ADCHEM th International Symposium on Advanced Control of Chemical Processes

Transcription

1 ADCHEM th International Symposium on Advanced Control of Chemical Processes Whistler, British Columbia, Canada June 7-10, 2015

2 Table of Contents Greetings from the NOC and IPC Chairs... 2 National Organizing Committee... 3 International Program Committee... 4 Plenary Talks... 6 Keynote Talks... 9 Instructions for Presenters & Session Chairs Local Attractions Sponsors Social Program & Announcements Technical Program Author Index Keyword Index Interview with Plenary Speakers Conference Venue Layout

3 Greetings from the NOC and IPC Chairs It is our pleasure to welcome you to the 2015 IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM 2015) in Whistler, British Columbia, Canada on behalf of the National Organizing Committee and International Program Committee. ADCHEM, one of the triennial meetings of the International Federation of Automatic Control, brings together researchers and practitioners to discuss recent developments in the control of chemical, biochemical, and related process systems. The program accommodates contributions from various application areas and methodologies including those outside the classical chemical process control. Special focus is put this year towards oil production as well as topics related to energy. Based on a rigorous reviewing process, the International Program Committee selected 216 papers for presentation. The program consists of 21 regular sessions, 4 invited sessions, 2 poster sessions, 1 roundtable discussion session, 12 keynote lectures (of which 5 are invited keynotes and 7 are selected from the contributions), and 3 plenary sessions. Following the tradition of ADCHEM, each morning begins with a plenary talk. Each day 4 keynotes are delivered, 2 in the morning and 2 in the afternoon. The regular and invited sessions are split in four parallel tracks, one in the morning and one in the afternoon. Poster presentations take place on Monday and Tuesday afternoon. The program is complemented by a roundtable discussion on Monday afternoon and very interesting preconference workshops that take place on Sunday, June 7. The social program consists of an opening reception on Sunday evening, a tour of the Squamish Lil wat Cultural Centre on Monday evening, the conference banquet on Tuesday evening, and a closing reception on Wednesday. The excellence of the program would not be possible without tremendous contributions of the NOC and IPC members, secretaries, invited session organizers, associate editors who organized review of the papers, and all the reviewers. We would also like to acknowledge the tremendous support from our conference sponsors. ADCHEM 2015 is sponsored by the IFAC Technical Committee on Chemical Process Control and co-sponsored by the IFAC Technical Committees on Non-linear Control Systems, Biosystems and Bioprocesses, and Fault Detection, Supervision and Safety of Technical Processes. All participants are invited to explore the wonderful landscape and nature of Whistler. Special guided tours and trips are planned following the afternoon sessions. There will be a number of volunteers throughout the conference who will be happy to provide help. Please do not hesitate to stop at the conference registration desk or contact any volunteer if you have questions or need help. We hope you will enjoy your stay in beautiful Whistler, British Columbia. Best regards, Biao Huang (NOC chair), on behalf of the NOC Rolf Findeisen (IPC chair), on behalf of the IPC 2

4 National Organizing Committee NOC Chair Biao Huang University of Alberta Canada NOC Co-Chair Bhushan Gopaluni University of British Columbia Canada NOC Industry Vice Chair Terry Chmelyk Spartan Control Canada Johan Backstrom Hector Budman Aris Espejo Enbo Feng Fraser Forbes Ramesh Kadali Zukui Li Kim McAuley Prashant Mhaskar Michel Perrier Vinay Prasad Sirish Shah Elizabeth Adolf Leanne Swekla Honeywell University of Waterloo Syncrude Suncor University of Alberta Suncor Energy University of Alberta Queen s University McMaster University École Polytechnique de Montréal University of Alberta University of Alberta University of Alberta Independent Organizer 3

5 International Program Committee IPC Chair Rolf Findeisen Otto-von-Guericke University Magdeburg Germany IPC Co-Chair Martin Guay Queen s University Canada IPC Industry Co-Chair Don Bartusiak ExxonMobil Chemical Company USA Area Co-Chairs Zoltan Nagy (USA) Batch Process Modelling Martin Mönnigmann (GER) Model-based Control Martha Grover (USA) Modelling and Identification Ravindra Gudi (IND) Scheduling and Optimization Claudio Scali (ITA) Process and Control Monitoring Manabu Kano (JPN) Process Applications Ulrike Krewer (GER) Energy Processes and Control Eric Bullinger (GER) Modelling and Control of Biomedical Systems 4

6 IPC Members Frank Allgöwer (GER) Yaman Arkun (TUR) Jia Bao (AUS) Wayne Bequette (USA) Luis Bergh (CHI) Dominique Bonvin (SUI) Richard Braatz (USA) Jesús Alvarez Calderón (MEX) Eduardo Camacho (ESP) Benoit Chachuat (GBR) Changjian Cheng (CHN) Jean-Pierre Corriou (FRA) Cesar de Prada (ESP) Yongsheng Ding (CHN) Denis Dochain (BEL) Carl Duchesne (CAN) Stephen P. Duncan (GBR) Sebastian Engell (GER) Mirsolav Fikar (SVK) Bjarne Foss (NOR) Furong Gao (HKG) Christos Georgakis (USA) Veit Hagenmeyer (GER) Juergen Hahn (USA) Katalin Hangos (HUN) Morten Hovd (NOR) Hsiao-Ping Huang (TPE) Jakob Kjabsted Huusom (DEN) Lars Imsland (NOR) Elling W. Jacobsen (SWE) Masako Kishida (NZL) Costas Kravaris (GRE) Jay Lee (KOR) Jong-Min Lee (KOR) Xiang Li (CAN) Shaoyuan Li (CHN) Daniel Limon (ESP) Fei Liu (CHN) Wolfgang Marquardt (GER) Bernard Maschke (FRA) Jaime A. Moreno (MEX) Michela Mulas (FIN) Ahmet Palazoglu (USA) Gabriele Pannoccia (ITA) Robert S. Parker (USA) Stratos Pistikopoulos (GBR) Joe Qin (USA) Josa Ragot (FRA) Davide Raimondo (ITA) G.P. Rangaiah (SIN) R. Rengasamy (IND/USA) Riccardo Scattolini (ITA) Ilse Smets (BEL) Masoud Soroush (USA) Stefan Streif (GER) Hongye Su (CHN) Moses Tade (AUS) Robert Tenno (FIN) Jorge Trierweiler (BRA) Paul Van den Hof (NLD) Alain Vande Wouwer (BEL) Wei Wang (CHN) Adrian George Wills (AUS) Hong Yue (GBR) 5

7 Plenary Talks 1. Platform for Advanced Control and Estimation (PACE): Shell's and Yokogawa's Next Generation Advanced Process Control Technology Barry Cott Shell Global Solutions, The Netherlands Abstract: Every ten years or so, Shell has looked to refresh its Advanced Process Control (APC) technology. The last major technology upgrade occurred in 2003 when Shell, along with our APC alliance partner, Yokogawa, released SMOCPro (MPC) and RQEPro (quality estimation). In 2011, Shell and Yokogawa agreed to initiate the development of our next-generation APC technology. Brought to the market in 2015, the Platform for Advanced Control is leveraging our long combined experience in APC. Biography: Barry Cott has been with Shell for over 25 years in a variety of technical and engineering management roles in the process automation and control discipline. He is currently General Manager - Process Automation Control and Optimization Software in Shell's Projects and Technology organization, overseeing the development of innovative software technology including advanced process control. Barry holds a BASc and a MASc from the University of Waterloo and a Ph.D. from Imperial College, all in Chemical Engineering. He is a registered Professional Engineer in the Canadian provinces of Ontario and Alberta and received the 2007 DG Fisher Award from the Canadian Society for Chemical Engineering for contributions to systems and control engineering in Canada. Please see page 44 for our interview with Barry Cott. 6

8 2. Process monitoring in the era of big data Joe Qin The Chinese University of Hong Kong, Shenzhen Abstract: The recent interest in big data has shown up in almost all aspects of knowledge discovery; including engineering, medicine, business, commerce, finance, and even science to benefit from the power of big data. The Internet of Things, smart and wireless sensors, wireless communications, mobile devices, smart devices, and smart manufacturing make data an abundant source of information from which to derive knowledge and make decisions. For process engineering systems where processes, units, and equipment are designed with well-specified purposes under well-controlled operations, mechanistic models and principles are dependable. However, for the operation of emerging or abnormal situations that are not expected in the design, data become indispensable assets for the decision-making in safe and efficient operations. In this plenary we offer a perspective on the essence of process data analytics, how data have been effectively used in process operations and control, and new perspectives on how process systems operations might evolve to a paradigm of data-enhanced operations and control. In particular the focus is on the latent structure modeling of high dimensional and massive amount of data from which to explore interesting latent data structures for the purpose of process data analytics, including abnormal condition monitoring, inferential estimation, and predictions based on principal auto- and cross- correlations. The concept of principal time series modeling will be introduced. To conclude the talk, we give a future perspective in exploring the power of new machine learning techniques that have enjoyed tremendous development in two decades. Biography: Dr. S. Joe Qin obtained his B.S. and M.S. degrees in Automatic Control from Tsinghua University in Beijing, China, in 1984 and 1987, respectively, and his Ph.D. degree in Chemical Engineering from University of Maryland at College Park in He is the Vice President of the Chinese University of Hong Kong, Shenzhen, and is on leave from the position of Fluor Professor of Process Engineering at the Viterbi School of Engineering of the University of Southern California. Dr. Qin is a Fellow of IEEE and Fellow of the International Federation of Automatic Control (IFAC). He is a recipient of the National Science Foundation CAREER Award, the 2011 Northrop Grumman Best Teaching award at Viterbi School of Engineering, the DuPont Young Professor Award, Halliburton/Brown & Root Young Faculty Excellence Award, NSF-China Outstanding Young Investigator Award, Chang Jiang Professor of Tsinghua University, Thousand Talent Professor of the Northeastern University of China, and an IFAC Best Paper Prize for the model predictive control survey paper published in Control Engineering Practice. He is currently an Associate Editor for Journal of Process Control, IEEE Control Systems Magazine, and a Member of the Editorial Board for Journal of Chemometrics. He has published over 110 papers in SCI journals, with over 5700 ISI Web of Science citations and an h-index of 39. Dr. Qin s research interests include process data analytics, process monitoring and fault diagnosis, model predictive control, system identification, building energy optimization, semiconductor process control, and control performance monitoring. Please see page 48 for our interview with Joe Qin. 7

9 3. Set-Theoretic Approaches in Analysis, Estimation and Control of Nonlinear Systems Benoit Chachuat Imperial College London Abstract: This paper gives an overview of recent developments in set-theoretic methods for nonlinear systems, with a particular focus on the activities in our own research group. Central to these approaches is the ability to compute tight enclosures of the range of multivariate systems, e.g. using ellipsoidal calculus or higher-order inclusion techniques based on multivariate polynomials, as well as the ability to propagate these enclosures to enclose the trajectories of parametric or uncertain differential equations. We illustrate these developments with a range of applications, including the reachability analysis of nonlinear dynamic systems; the determination of all equilibrium points and bifurcations in a given state-space domain; and the solution of setmembership parameter estimation problems. We close the paper with a discussion about on-going research in tube-based methods for robust model predictive control. Biography: Benoit Chachuat is a Senior Lecturer in the Department of Chemical Engineering at Imperial College London and a member of the Centre of Process Systems Engineering (CPSE). He received his Ph.D. in Chemical Engineering from National Polytechnic Institute of Lorraine (INPL) in 2001, and he held post-doctoral positions at INRIA Sophia-Antipolis ( ), MIT ( ), and EPFL ( ). Prior to joining Imperial College in 2010, Benoit was an Assistant Professor at McMaster University. He currently serves as an Associate Editor for the Journal of Process Control and the Journal of Optimization Theory & Applications. He is a recipient of the 2014 Outstanding Young Researcher Award and 2015 Director Award from the CAST division of AIChE. Benoit's primary research focus is on the development of new methods and tools for optimization and control of complex process systems, with emphasis on global optimization and optimization-based process control. Current application areas in his group are on sustainable microalgae culture systems and resource recovery from wastewater. 8

10 Keynote Talks 1. Providing Ancillary Service with Commercial Buildings: The Swiss Perspective (invited) Ioannis Lymperopoulos, EPFL, Switzerland Faran Ahmed Qureshi, EPFL, Switzerland Truong Nghiem, Univ. of Pennsylvania, USA Ali Ahmadi Khatir, Swissgrid Ltd, Laufenburg, Switzerland Colin N. Jones, EPFL, Switzerland Abstract: Ancillary services constitute the cornerstone of the power grid. They allow for an efficient system operation, provide resilience to uncertainties and establish safeguards against unprecedented events. Their importance is growing due to the rise of grid decentralisation and integration of intermittent, renewable power sources, which lead to more variability and uncertainty in the system. Today, the vast share of ancillary services is provided by large generating units. An ongoing effort by research and business entities focuses on using variation of loads connected to the power grid in order to increase significantly the provision of such services, hopefully at a reduced cost. We examine here, from an economic perspective, the use of commercial buildings as ancillary service providers based on real prices from the Swiss electricity market. We calculate the effect of retail electrical prices on the economic performance of a building and find that for the rates charged in the least expensive cantons a single building can reduce its overall energy costs, when participating in the ancillary services market. For the high end of prices this gradually becomes prohibitive but can be alleviated for a building that has a need for electricity during nighttime hours, as well as daytime. Finally, we show, the counter-intuitive result that providing ancillary services can increase the comfort levels of a building at a decreased cost. 2. On-Line Maximization of Biogas Production in an Anaerobic Reactor Using a Pseudo- Super-Twisting Controller Alejandro Vargas, Univ. Nacional Autonoma De Mexico-UNAM Jaime A. Moreno, Univ. Nacional Autonoma De Mexico-UNAM Abstract: We consider an apparently oversimplified first order model of an anaerobic digester operated as a CSTR, where the dilution rate is the controlled input and the biogas production rate is the measured output. The parameters of this model are considered slowly time-varying. The output function depends on the only state (the substrate), and at any instant has a unique maximum. We propose a simple output-feedback controller based on the super-twisting algorithm combined with a state machine, which converges in a practical sense to this maximum. The controller was tested by simulations of an anarobic digester, maximizing the biogas production rate, showing very good results. 3. Economic Optimization of Spray Dryer Operation Using Nonlinear Model Predictive Control with State Estimation Lars Norbert Petersen, Tech. Univ. of Denmark John B. Jørgensen, Tech. Univ. of Denmark James B. Rawlings, Univ. of Wisconsin at Madison, USA Abstract: In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least squares method (ALS). We present a model for the spray drying plant and use this model for simulation as well as for prediction in the E-NMPC. The open-loop optimal control problem in the E-NMPC is solved using the single-shooting method combined with a quasi- Newton Sequential Quadratic Programming (SQP) algorithm and the adjoint method for computation of gradients. We evaluate the economic performance when unmeasured disturbances 9

11 are present. By simulation, we demonstrate that the E-NMPC improves the profit of spray drying by 17% compared to conventional PI control. 4. A Stable Two-Time Dimensional (2D) Model Predictive Control with Zero Terminal State Constraints for Constrained Batch Processes Jingyi Lu, Hong Kong Univ. of Sci. & Tech Zhixing Cao, Hong Kong Univ. of Sci. & Tech Furong Gao, Hong Kong Univ. of Sci. & Tech Abstract: Batch processes are of great importance in process industry. However, the control algorithm design is difficult for those with constraints. This is because stability and recursive feasibility along directions of time and batch should be guaranteed simultaneously. In this paper, a stable model predictive control strategy with zero terminal state constraints is proposed. Stability and recursive feasibility along two directions are guaranteed and proved. Simulation results are given to show the effectiveness of the algorithm. 5. Latent Variable Models and Big Data in the Process Industries (invited) John F. Macgregor, ProSensus, Inc Mark-John Bruwer, ProSensus, Inc Ivan Miletic, ProSensus, Inc Marlene Cardin, ProSensus, Inc Zheng Liu, ProSensus, Inc Abstract: In the process industries Big Data has been around since the introduction of computer control systems, advanced sensors, and databases. Although process data may not really be BIG in comparison to other areas such as communications, they are often complex in structure, and the information that we wish to extract from them is often subtle. Multivariate latent variable regression models offer many unique properties that make them well suited for the analysis of historical industrial data. These properties and use of these models are illustrated with applications to the analysis, monitoring. optimization and control of batch processes, and to the extraction of information from on-line multi-spectral images. 6. On the Design of Economic NMPC Based on an Exact Turnpike Property Timm Faulwasser, EPFL, Switzerland Dominique Bonvin, EPFL, Switzerland Abstract: We discuss the design of sampled-data economic nonlinear model predictive control schemes for continuous-time systems. We present novel sufficient convergence conditions that do not require any kind of terminal constraints nor terminal penalties. Instead, the proposed convergence conditions are based on an exact turnpike property of the underlying optimal control problem. We prove that, in the presence of state constraints, the existence of an exact turnpike implies recursive feasibility of the optimization. We draw upon the example of optimal fish harvest to illustrate our findings. 7. Analysis of Problems Induced by Imprecise Dating of Measurements in Oil and Gas Production Nicolas Petit, MINES ParisTech, France Abstract: In this paper we discuss the negative impact on monitoring algorithms of working with imprecisely dated data. Two examples from the world of the oil & gas industry are presented and serve to illustrate that this problem can be of practical importance. First analytical results show that when signals with significant time variations are monitored, the impact of dating of measurements can be as troublesome (or even worse) than measurement noises. 8. A Multiobjective Optimization Perspective on the Stability of Economic MPC (invited) 10

12 Victor M. Zavala, Argonne National Lab, USA Abstract: We interpret economic MPC as a scheme that trades off economic performance and stability. We use this notion to design an economic MPC controller that exploits the inherent robustness of a stable auxiliary MPC controller to enhance economic performance. Specifically, we incorporate a flexible stabilizing constraint to the economic MPC formulation that preserves stability of the auxiliary controller. We use multiobjective optimization concepts to argue that the dual variable of the stabilizing constraint can be interpreted as a price of stability and we establish an equivalence between the proposed controller and regularized economic MPC controllers. We demonstrate that nontrivial gains in economic performance can be achieved without compromising stability. 9. Control Challenges in Synthetic Biology (invited) Christopher V. Rao, Univ. of Illinois at Urbana-Champaign Abstract: Automation is increasingly being employed in the life sciences. New control problems are arising as a result, few with simple off-the-shelf solutions. This paper discusses some of the scheduling and control problems associated with automation in synthetic biology. It specifically focuses on the challenges associated with robotics, drawing heavily from our own experiences at the University of Illinois at Urbana-Champaign. No solution are presented and only the problems discussed. The goal is to motivate research in the process systems engineering community to solve problems in this new field. 10. Zone Model Predictive Control and Moving Horizon Estimation for the Regulation of Blood Glucose in Critical Care Patients Timothy Knab, Univ. of Pittsburgh Gilles Clermont, Univ. of Pittsburgh Robert S. Parker, Univ. of Pittsburgh Abstract: Critically ill patients commonly suffer from stress hyperglycemia, or elevated glucose levels, following injury or disease. Hypoglycemia, or low glucose level, is a frequent and serious complication of treating hyperglycemia. In order to reduce the incidence of hyper- and hypoglycemia, a linear zone model-predictive controller with moving horizon state estimation and output regulation is developed. Critical care patient data from an observational study was used to construct virtual patients. Closed-loop control in these virtual patients, versus clinical standard of practice, results in a substantial increase in time spent in the target glucose zone and significant reductions in both hyperglycemia and hypoglycemia. Overall, the proposed controller significantly enhances targeted glucose control in critically ill patients in silico, which may translate to improved clinical decision making and patient outcomes in the clinic. 11. Artificial Pancreas: From In-Silico to In-Vivo (invited) Mirko Messori, Univ. of Pavia, Italy Claudio Cobelli, Univ. of Padova, Italy Lalo Magni, Univ. of Pavia, Italy Abstract: Type 1 diabetes is a disease caused by an autoimmune reaction. The Artificial Pancreas (AP) is an automatic closed-loop system composed of a subcutaneous glucose sensor, a subcutaneous insulin pump and a device on which a control algorithm and a human interface are implemented. The last years have seen an accelerated improvement of these three components that became more reliable and compact, making the system safer, wearable, and usable in real life. An overview on AP and its components is presented together with an introduction on the insilico tools used to develop and tune the control algorithm and to make pre-clinical tests. Particular attention is devoted to the design of a Model Predictive Control, to the choice of the model and of the constraints, and to the definition of the most relevant performance indices. Most of the choices have been driven by the experience gained by both in-silico and in-vivo trials. In-silico experiments 11

13 involved thousand of hours of simulations on the Food and Drug Administration accepted simulator equipped with 100 adult virtual patients. In-vivo experiments, of which a complete list is presented, involved about forty thousand hours of trials, first, conducted in a clinical environment and, then, at home. 12. Design of a Smart Adaptive Control System Takuya Kinoshita, Hiroshima Univ., Japan Toru Yamamoto, Hiroshima Univ., Japan Abstract: In industrial processes, it is necessary to maintain the user-specified control performance in order to achieve desired productivity. This paper describes a design scheme of smart adaptive controller based on mentioned strategy. In our proposed method, variance of control error and input are evaluated on-line. Moreover, control parameters are adjusted only when the user-specified control performance is not obtained. Control parameters are calculated directly from closed-loop data and they are adjusted by 1-parameter tuning. The effectiveness of the proposed method is verified by using a simulation example and experiment of temperature control system. 12

14 Instructions for Presenters & Session Chairs 1. Oral Presentations The allocated time for the talks are as follows: Type Presentation Discussion Plenary 50 minutes 10 minutes Keynote 25 minutes 5 minutes Regular 17 minutes 3 minutes A laptop will be available for presentations with MS-Office PowerPoint 2010 or later version, or Adobe Acrobat X format. Presenters should transfer their files to the laptop at the venue of their presentation as early as possible. Preferable times are during coffee, lunch and inter-session breaks. A student volunteer will be available to assist the presenters. Presenters are requested to submit a short biography to the Session Chair, 5 minutes before the beginning of the session. The biography should include at least your title, name and affiliation. 2. Poster Presentations The poster should be in portrait layout and A1 size (594mm (W) x 841mm (H) /23.3in (W) x 35in (H)). Posters should be put up by 1:30 PM on the presentation day and removed right after the session ends. Board pins and Velcro tape will be available on-site. Posters are to be put up according to the numbering on the poster panels. Authors should be present during the poster session to explain their work and to interact with fellow attendees. 3. Session Chairs Please take note of the day/time/venue of the session that you are chairing in the program booklet. On the day of the session that you are chairing, obtain any changes to the program from the Secretariat at the Registration Desk. Before the start of the session, collect the biographical information of the presenting authors. Use this information to introduce the speaker before his/her presentation. Be present in the room where the session is to be held 10 minutes before the start of the session and check that all the presentations have been copied on the notebook provided at the venue. Remind the presenting author about the time available for their presentation; see Instructions to Authors for details. Remind the authors at the 2-minute mark (e.g., at the 15th minute of presentation for regular presentations) to make their concluding remarks. Please ensure that there is sufficient time for discussion. At the end of the session, fill in the session summary report with a nomination for best presentation award and drop it off at the registration desk. In case of no-show or if a talk ends early, do not advance the presentations. The additional time can be used for discussions related to papers presented earlier in the session. 13

15 Local Attractions Whistler is a Canadian resort town located in the Coast Mountains in the province of British Columbia. Whistler features two majestic mountains with a vibrant base village, epic skiing and snowboarding, four championship golf courses, unbeatable shopping, restaurants and bars, accommodation to suit every budget, hiking trails, spas and arguably the best mountain bike park in the world. Whistler was the Host Mountain Resort of the Vancouver 2010 Winter Olympic and Paralypmic Games. Whistler's vibrant arts and culture scene flourishes year round with a multitude of cultural offerings from engaging art exhibitions, lively music and dance performances and First Nations culture to international film and culinary events. Squamish Lil wat Cultural Centre. The Squamish Nation and Lil wat Nation have coexisted respectfully as neighbors since time immemorial. They have thrived on the bounty of the ocean, the rivers, and the land. Their cultures are grounded in rich, ancient traditions, and continue to grow and evolve in a modern world. The Squamish Lil wat Cultural Centre in Whistler BC (where mountains, rivers and people meet), embodies the spirit of partnership between two unique Nations who wish to preserve, grow and share our traditional cultures. It stands as testimony to our proud heritage from time immemorial to the present. To learn more about Whistler's cultural institutions and offerings, please visit Activities for tourists in Whistler are limitless and include: Hiking. Alpine Hiking on Whistler and Blackcomb Mountains. Whistler and Blackcomb Mountains boast hiking trails with incredible views. Choose from short, family friendly strolls on wide paths to more advanced hikes to lakes, glaciers and alpine meadows. Keep your eyes open for chipmunks and marmots, and make sure you keep a camera handy for capturing the rugged mountain vistas. Tree Adventure Tours. Ziptrek offers an entertaining combination of high-wire adventure and ecological exploration on a choice of 3 guided zipline tours. For those who are looking for a light adventure, TreeTrek Canopy Walk offers a guided interpretive adventure across a stunning network of suspension bridges, suspended stairways, boardwalks and ground based trails, with no zipping required. Nestled in between Whistler and Blackcomb Mountains, above Fitzsimmons Creek, Ziptrek's tour area boasts spectacular tree top vistas. Superfly is home to Canada's longest, most epic ziplines! With cutting edge zipline technology designed to whiz the forest canopies of Whistler, into a bright green blur, and treetop rope adventures charged with challenge and adrenaline, Superfly is big airborne fun for everyone. White water rafting. Experience the ultimate white water rafting adventure with convenient pickups from Whistler. It is great for everyone from adventure junkies to families! 14

16 Sponsors KEY SPONSORS Tech Futures is part of Alberta s research and innovation system and is helping build healthy, sustainable businesses in the province. Through a suite of programs and services directed towards entrepreneurs, companies, researchers and investors, Tech Futures is preparing Alberta for a next generation economy. From steel in the 19th century, to electrical distribution and automation in the 20th and energy management in the 21st, Schneider Electric has always been driven by an international, innovative and responsible mindset to shape the transformation of the industry it was evolving in. In 1967, Suncor pioneered commercial development of Canada s oil sands one of the largest petroleum resource basins in the world. Since then, Suncor has grown to become a globally competitive integrated energy company with a balanced portfolio of high-quality assets, a strong balance sheet and significant growth prospects. Across our operations, they intend to achieve production of one million barrels of oil equivalent per day. Spartan Controls offers a complete range of products and services to meet any process control challenge. For almost 50 years, Spartan has served the industry with quality products, technical expertise, after-sales support, on-site consultation, service, and training. SUSTAINING SPONSORS Honeywell invents and manufactures technologies to address some of the world s toughest challenges initiated by revolutionary macrotrends in science, technology and society. Honeywell creates solutions to improve the quality of life of people around the globe: generating clean, healthy energy and using it more efficiently. Increasing safety and security. The MathWorks, Inc. (branded simply as MathWorks) is an American privately held corporation that specializes in mathematical computing software. Its major products include MATLAB and Simulink. As of April 2014, it employed over 3,000 people worldwide with 70% located at the company s headquarters in Natick, Massachusetts, USA. 15

17 Social Program & Announcements Sunday (June 7) Opening reception, Valley Voyer/Garibaldi, 19:30-21:30 Monday (June 8) JPC Subject Editor Meeting, Spearhead A/B, 12:00-13:00 Panel discussion,, 15:40-17:00 Tour of the Squamish Cultural Centre, 19:30-21:30 Tuesday (June 9) JPC Editorial Board Meeting, Spearhead A/B, 12:20-13:20 Mathworks session,, 16:20-17:00 Conference Banquet, Grand Foyer, 19:30-21:30 Wednesday (June 10) TC 6.1 meeting, Spearhead A/B, 12:20-13:20 16

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19 13:30-17:30 SuW1 Spearhead A Alarm Systems: Quantitative Analysis and Design Program at a Glance (Sunday June 7, 2015) Track 1 Track 2 Track 3 Track 4 Track 5 13:30-17:30 SuW2 13:30-17:30 SuW3 13:30-17:30 SuW4 Spearhead B Wedgemount A Wedgemount B Model-Based Estimation, Fault Nonlinear Programming Strategies Discrete SISO Controller Design: Diagnosis, and Control of Uncertain for Dynamic Process Optimization: The Time Series Approach Nonlinear Systems Using Off-Line and On-Line Polynomial Chaos 19:30-21:30 SuRPl Valley Voyer/Garibalid Opening Reception 13:30-17:30 SuW5 Black Tusk Multi-Block, Multi-Set, Multi-Level, and Data Fusion Models 18

20 Program at a Glance (Monday June 8, 2015) Track 1 Track 2 Track 3 Track 4 08:00-08:10 MoOP Opening 08:10-09:10 MoPLP 09:10-09:40 MoKM1 Keynote 1 10:00-12:00 MoM1 Economic Predictive Control 09:10-09:40 MoKM2 Spearhead Keynote 2 10:00-12:00 MoM2 Spearhead Oil and Gas Plenary 1 09:40-10:00 MoCMP Garibaldi Coffee Mo 10:00-12:00 MoM3 Wedgemount Modeling and Identification I 10:00-12:00 MoM4 Black Tusk State and Parameter Estimation 13:00-15:00 MoA1 Optimization and Control 13:00-15:00 MoA2 Spearhead Control and Optimization Challenges in Oil and Gas Industries 12:00-13:00 MoLP Garibaldi Lunch Mo 13:00-15:00 MoA3 Wedgemount Modeling and Identification II 13:00-15:00 MoA4 Black Tusk Batch Processes 15:40-17:00 MoRT1 Roundtable Discussion 17:00-17:30 MoKA1 Keynote 3 15:00-17:00 MoP2 Garibaldi Poster 1 17:00-17:30 MoKA2 Spearhead Keynote 4 19:30-21:30 MoRP Squamish Cultural Centre Visit 19

21 Program at a Glance (Tuesday June 9, 2015) Track 1 Track 2 Track 3 Track 4 08:30-09:30 TuPLP 09:30-10:00 TuKM1 Keynote 5 10:20-12:20 TuM1 Predictive Control Applications 09:30-10:00 TuKM2 Spearhead Keynote 6 10:20-12:20 TuM2 Spearhead Energy Processes and Control I Plenary 2 10:00-10:20 TuCMP Garibaldi Coffee Tu 10:20-12:20 TuM3 Wedgemount Process and Control Monitoring I 10:20-12:20 TuM4 Black Tusk Alarm Systems Design and Monitoring 13:30-15:30 TuA1 Extremum Seeking and Adaptive Control 13:30-15:30 TuA2 Spearhead Energy Processes and Control II 12:20-13:30 TuLP Garibaldi Lunch Tu 13:30-15:30 TuA3 Wedgemount Process and Control Monitoring II 16:20-17:00 TuMW1 Mathworks 17:00-17:30 TuKA1 Keynote 7 15:30-17:00 TuP2 Garibaldi Poster 2 17:00-17:30 TuKA2 Spearhead Keynote 8 19:30-23:00 TuRP Grand Foyer Conference Banquet 20

22 Program at a Glance (Wednesday June 10, 2015) Track 1 Track 2 Track 3 Track 4 08:30-09:30 WePLP 09:30-10:00 WeKM1 Keynote 9 10:20-12:20 WeM1 Robust Predictive Control 09:30-10:00 WeKM2 Spearhead Keynote 10 10:20-12:20 WeM2 Spearhead Thermodynamics and Process Control Plenary 3 10:00-10:20 WeCMP Garibaldi Coffee WeM 10:20-12:20 WeM3 Wedgemount Biological Systems 10:20-12:20 WeM4 Black Tusk Process Applications 13:30-15:30 WeA1 Scheduling, Optimization, and Control 13:30-15:30 WeA2 Spearhead Modeling, Control and Optimization of Energy Generating Systems 12:20-13:30 WeLP Garibaldi Lunch We 13:30-15:30 WeA3 Wedgemount Modeling and Optimization of Biological Systems 13:30-15:30 WeA4 Black Tusk Fault Detection and Identification 15:50-16:20 WeKA1 Keynote 11 15:50-16:20 WeKA2 Spearhead Keynote 12 15:30-15:50 WeCAP Garibaldi Coffee WeA 16:20-17:30 WeClosingP Closing Ceremony 21

23 Technical Program Liu, Su Zhang, Jing Liu, Jinfeng MoPLP Monday June 8, 2015 Plenary 1 (Plenary Session) Chair: Bartusiak, Donald ExxonMobil Res. & Engineering Co-Chair: Huang, Biao 08:10-09:10 MoPLP.1 Platform for Advanced Control and Estimation (PACE): Shell's and Yokogawa's Next Generation Advanced Process Control Technology, pp Amrit, Rishi Canney, William Carrette, Pierre Linn, Richard Martinez, Alex Singh, Abhay Skrovanek, Thomas Valiquette, Jean Zhou, Jack Cott, Barry MoKM1 Keynote 1 (Keynote Session) Chair: Krewer, Ulrike Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions (US) Inc Shell Global Solutions International BV TU Braunschweig Co-Chair: Lee, Jay H. KAIST 09:10-09:40 MoKM1.1 Providing Ancillary Service with Commercial Buildings: The Swiss Perspective, pp Lymperopoulos, Ioannis Qureshi, Faran Ahmed Nghiem, Truong Khatir, Ali Ahmadi Jones, Colin N. MoKM2 Keynote 2 (Keynote Session) Chair: Li, Zukui Epfl Epfl Univ. of Pennsylvania Swissgrid Ltd, Laufenburg Epfl Spearhead Co-Chair: Dochain, Denis Univ. Catholique de Louvain 09:10-09:40 MoKM2.1 On-Line Maximization of Biogas Production in an Anaerobic Reactor Using a Pseudo-Super-Twisting Controller, pp MoM1 Vargas, Alejandro Moreno, Jaime A. Economic Predictive Control (Regular Session) Chair: Allgower, Frank Univ. Nacional Autonoma De Mexico-UNAM Univ. Nacional Autonoma De Mexico-UNAM Univ. of Stuttgart Co-Chair: Lucia, Sergio OvG Univ. of Magdeburg 10:00-10:20 MoM1.1 Economic MPC with Terminal Cost and Application to Oilsand Separation, pp :20-10:40 MoM1.2 Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures, pp Anderson, Timothy L. Ucla Ellis, Matthew Ucla Christofides, Panagiotis D. Univ. of California at Los Angeles 10:40-11:00 MoM1.3 Economics-Oriented NMPC of Two-Stage-Riser Catalytic Pyrolysis Processes for Maximizing Propylene Yield, pp Wang, Ping China Univ. of Petroleum Tian, Xuemin China Univ. of Petroleum Yang, Chaohe China Univ. of Petroleum Yuan, Zhihong Auburn Univ 11:00-11:20 MoM1.4 Economic Multi-Stage Output Feedback NMPC Using the Unscented Kalman Filter, pp Subramanian, Sankaranarayanan Lucia, Sergio TU Dortmund Otto-Von-Guericke Univ. Magdeburg TU Dortmund Engell, Sebastian 11:20-11:40 MoM1.5 Average Constraints in Robust Economic Model Predictive Control, pp Bayer, Florian Univ. of Stuttgart Muller, Matthias A. Univ. of Stuttgart Allgower, Frank Univ. of Stuttgart 11:40-12:00 MoM1.6 Scenario-Based Model Predictive Control: Recursive Feasibility and Stability, pp Maiworm, Michael Bäthge, Tobias Findeisen, Rolf MoM2 Oil and Gas (Regular Session) Chair: Li, Zukui Co-Chair: Nikoofard, Amirhossein Otto-Von-Guericke Univ. Magdeburg Otto-Von-Guericke Univ. Magdeburg Otto-Von-Guericke Univ. Magdeburg Spearhead Norwegian Univ. of Science and Tech. 10:00-10:20 MoM2.1 Well Placement Optimization with Geological Uncertainty Reduction, pp Rahim, Shahed Li, Zukui 10:20-10:40 MoM2.2 Froth Pipeline Water Content Estimation and Control, pp Miao, Yu Xu, Fangwei Zheng, Yi Huang, Biao MacGowan, John Syncrude Canada Ltd Shanghai Jiao Tong Univ Syncrude Canada Ltd 22

24 Espejo, Aris Syncrude Canada Ltd 10:40-11:00 MoM2.3 Evaluation of Lyapunov-Based Adaptive Observer Using Low-Order Lumped Model for Estimation of Production Index in Under-Balanced Drilling, pp Nikoofard, Amirhossein Norwegian Univ. of Science and Tech Johansen, Tor Arne Norwegian Univ. of Science and Tech Kaasa, Glenn-Ole Kelda Drilling Controls 11:00-11:20 MoM2.4 Pipeline Leak Detection Using Particle Filters, pp Arifin, B. M. Sirajeel Li, Zukui Shah, Sirish L. 11:20-11:40 MoM2.5 Infinite-Dimensional Observer for Process Monitoring in Managed Pressure Drilling, pp Hasan, Agus Norwegian Univ. of Science and Tech 11:40-12:00 MoM2.6 Stochastic Proxy Modelling for Coalbed Methane Production Using Orthogonal Polynomials, pp Senthamaraikkannan, Gouthami Prasad, Vinay Gates, Ian MoM3 Modeling and Identification I (Regular Session) Chair: Mesbah, Ali Univ. of Calgary Wedgemount Univ. of California, Berkeley Co-Chair: Prasad, Vinay 10:00-10:20 MoM3.1 Continuous-Time Enclosures for Uncertain Implicit Ordinary Differential Equations, pp Rajyaguru, Jai Imperial Coll. London Villanueva, Mario E. Imperial Coll. London Houska, Boris ShanghaiTech Univ Chachuat, Benoit Imperial Coll. London 10:20-10:40 MoM3.2 A Probabilistic Approach to Robust Optimal Experiment Design with Chance Constraints, pp Mesbah, Ali Univ. of California, Berkeley Streif, Stefan Ilmenau Univ. of Tech 10:40-11:00 MoM3.3 Robust Design of Experiments Using Constrained Stochastic Optimization, pp Popli, Khushaal Prasad, Vinay 11:00-11:20 MoM3.4 Model Migration through Bayesian Adjustments, pp Luo, Linkai Hong Kong Univ. of Sci. & Tech Gao, Furong Hong Kong Univ. of Sci. & Tech 11:20-11:40 MoM3.5 Dynamic-Inner Partial Least Squares for Dynamic Data Modeling, pp Dong, Yining Qin, S. Joe Univ. of Southern California Univ. of Southern California 11:40-12:00 MoM3.6 Nearest Correlation Louvain Method for Fast and Good Selection of Input Variables of Statistical Model, pp Uchimaru, Taku Hazama, Koji Fujiwara, Koichi Kano, Manabu MoM4 State and Parameter Estimation (Regular Session) Chair: Dubljevic, Stevan Co-Chair: Vande Wouwer, Alain Kyoto Univ Kyoto Univ Kyoto Univ Kyoto Univ Black Tusk Unversity of Alberta Univ. de Mons 10:00-10:20 MoM4.1 State and Input Estimation of an Anaerobic Digestion Reactor Using a Continuous-Discrete Unknown Input Observer, pp Rocha-Cózatl, Edmundo Univ. Nacional Autonoma De Mexico Sbarciog, Mihaela Univ. De Mons Dewasme, Laurent Univ. De Mons Moreno, Jaime A. Univ. Nacional Autonoma De Mexico Vande Wouwer, Alain Univ. De Mons 10:20-10:40 MoM4.2 Moving-Horizon Predictive Input Design for Closed-Loop Identification, pp Yousefi, Mahdi Univ. of British Columbia Rippon, Lee Univ. of British Columbia Forbes, Michael Gregory Honeywell Gopaluni, Bhushan Univ. of British Columbia Loewen, Philip D. Univ. of British Columbia Dumont, Guy Univ. of British Columbia Backstrom, Johan Honeywell Measurex Inc 10:40-11:00 MoM4.3 Observer Design Using Potential Based Realizations, pp Guay, Martin Queen's Univ Bennett, Ryan Queen's Univ Hudon, Nicolas Univ. Catholique De Louvain 11:00-11:20 MoM4.4 A Bayesian Method for Estimating Parameters in Stochastic Differential Equations, pp Karimi, Hadiseh Queen S Univ McAuley, K.B. Queen S Univ 11:20-11:40 MoM4.5 Optimal State Estimation for Linear Systems with State Constraints, pp Xu, Xiaodong Huang, Biao Dubljevic, Stevan 11:40-12:00 MoM4.6 Distributed Adaptive High-Gain Extended Kalman Filtering for Nonlinear Systems, pp Rashedi, Mohammad Liu, Jinfeng Huang, Biao 23

25 MoA1 Optimization and Control (Regular Session) Chair: Faulwasser, Timm EPFL Co-Chair: Lee, Jay H. KAIST 13:00-13:20 MoA1.1 Model-Based On-Line Optimization Framework for Semi- Batch Polymerization Reactors, pp Jung, Tae Yeong Kaist Nie, Yisu The Dow Chemical Company Lee, Jay H. Kaist Biegler, Lorenz T. Carnegie Mellon Univ 13:20-13:40 MoA1.2 On Bifurcations of the Zero Dynamics - Connecting Steady-State Optimality to Process Dynamics, pp Trollberg, Olle KTH Royal Inst. of Tech Jacobsen, Elling W. KTH Royal Inst. of Tech 13:40-14:00 MoA1.3 On Handling Cost Gradient Uncertainty in Real-Time Optimization, pp Singhal, Martand Epfl Faulwasser, Timm Epfl Bonvin, Dominique Epfl 14:00-14:20 MoA1.4 Comparison of Modifier Adaptation Schemes in Real-Time Optimization, pp Gao, Weihua TU Dortmund Wenzel, Simon TU Dortmund Engell, Sebastian TU Dortmund 14:20-14:40 MoA1.5 Integration of Process Design and Control Using Hierarchical Control Structure, pp Zhou, Mengfei Zhejiang Univ. of Tech Li, Long Zhejiang Univ. of Tech Xie, Lei Zhejiang Univ. of Tech Cai, Yijun Zhejiang Univ. of Tech Pan, Haitian Zhejiang Univ. of Tech 14:40-15:00 MoA1.6 Anti-Fouling Control of Plug-Flow Crystallization Via Heating and Cooling Cycle, pp Koswara, Andy Nagy, Zoltan K. MoA2 Control and Optimization Challenges in Oil and Gas Industries (Invited Session) Chair: Budman, Hector M. Purdue Univ Purdue Univ Spearhead Univ. of Waterloo Co-Chair: Bartusiak, Donald ExxonMobil Res. & Engineering 13:00-13:20 MoA2.1 Spectroscopic Measurements in Oil Sands Industry - from Laboratories to Real-Time Applications (I), pp Feng, Enbo Suncor Energy Inc Domlan, Elom Ayih Kadali, Ramesh Suncor Energy Inc 13:20-13:40 MoA2.2 Refinery Optimization Integrated with a Nonlinear Crude Distillation Unit Model (I), pp Yang, Yu Barton, Paul Massachusetts Inst. of Tech Massachusetts Inst. of Tech 24 13:40-14:00 MoA2.3 Adaptive Soft Sensing and On-Line Estimation of the Critical Minimum Velocity with Application to an Oil Sand Primary Separation Vessel (I), pp Sammaknejad, Nima Huang, Biao Sanders, R. Sean Miao, Yu Xu, Fangwei Syncrude Canada Ltd Espejo, Aris Syncrude Canada Ltd 14:00-14:20 MoA2.4 Production Optimization under Uncertainty - Applied to Petroleum Production (I), pp Hanssen, Kristian Gaustad Norwegian Univ. of Science & Tech Foss, Bjarne Norwegian Univ. of Science & Tech 14:20-14:40 MoA2.5 Modifier-Adaptation Methodology for RTO Applied to Distillation Columns (I), pp Rodríguez-Blanco, Tania Univ. of Valladolid Sarabia, Daniel Univ. of Burgos Navia, Daniel Univ. Técnica Federico Santa María de Prada, Cesar Univ. of Valladolid 14:40-15:00 MoA2.6 Inclusion of Long-Term Production Planning/Scheduling into Real-Time Optimization (I), pp Kumar, Divya Chen, Ye MoA3 Esmaili, Ali Modeling and Identification II (Regular Session) Chair: McAuley, K.B. Univ. of Waterloo Process Data Tech. Air Products and Chemicals Process Data Tech. Air Products and Chemicals Wedgemount Queen's Univ. Co-Chair: Bajcinca, Naim Max Planck Inst. 13:00-13:20 MoA3.1 A Comparative Study on Improved DPLS Soft Sensor Models Applied to a Crude Distillation Unit, pp Shang, Chao Tsinghua Univ Gao, Xinqing Tsinghua Univ Yang, Fan Tsinghua Univ Lyu, Wenxiang Tsinghua Univ Huang, Dexian Tsinghua Univ 13:20-13:40 MoA3.2 Generalizing ODE Modeling Structure for Multivariate Systems with Distributed Parameters, pp Bajcinca, Naim Max Planck Inst. Magdeburg Hofmann, Steffen Max Planck Inst. Magdeburg Eisenschmidt, Holger Max Planck Inst. Magdeburg Sundmacher, Kai Max Planck Inst. Magdeburg 13:40-14:00 MoA3.3 Time-Series Prediction Modelling Based on an Efficient Self-Organization Learning Neural Network, pp Yang, Gang East China Jiaotong Univ Yang, Hui East China Jiaotong Univ Dai, Lizhen East China Jiaotong Univ 14:00-14:20 MoA3.4

26 Identification of Time-Delay Systems: A State-Space Realization Approach, pp Lima, Rafael Univ. Federal De Campina Grande Barros, Péricles R. Univ. Federal De Campina Grande 14:20-14:40 MoA3.5 A Calibration Model Maintenance Road Map, pp Wise, Barry M. Eigenvector Res. Inc Roginski, Robert T. Eigenvector Res. Inc 14:40-15:00 MoA3.6 Incremental Model Identification of Distributed Two-Phase Reaction Systems, pp Rodrigues, Diogo Billeter, Julien Bonvin, Dominique MoA4 Batch Processes (Regular Session) Chair: Gao, Furong Epfl Epfl Epfl Black Tusk Hong Kong Univ. of Sci & Tech. Co-Chair: Kwon, Joseph UCLA 13:00-13:20 MoA4.1 Integrated Optimization Based on Transition Tracking Analysis for Batch Processes, pp Qin, Yan Zhejiang Univ Zhao, Chunhui Zhejiang Univ Gao, Furong Hong Kong Univ. of Sci & Tech 13:20-13:40 MoA4.2 On Operation of PECVD of Thin Film Solar Cells, pp Crose, Marquis Ucla Kwon, Joseph Ucla Nayhouse, Michael Ucla Ni, Dong Zhejiang Univ Christofides, Panagiotis D. Univ. of California at Los Angeles 13:40-14:00 MoA4.3 Experimental Validation of Robust Process Design and Control Based on Gaussian Mixture Densities, pp Rossner, Niko Tech. Univ. Berlin King, Rudibert Tech. Univ. Berlin 14:00-14:20 MoA4.4 Data-Driven Two-Dimensional LQG Benchmark Based Performance Assessment for Batch Processes under ILC, pp Wei, Shaolong Beijing Univ. of Chemical Tech Cheng, Jinxu Beijing Univ. of Chemical Tech Wang, Youqing Beijing Univ. of Chemical Tech 14:20-14:40 MoA4.5 Optimization of Two-Stage Cooling Profile in Unseeded Batch Crystallization, pp King, Jared Georgia Inst. of Tech Li, Huayu Georgia Inst. of Tech Grover, Martha Georgia Inst. of Tech Kawajiri, Yoshiaki Georgia Inst. of Tech Rousseau, Ronald W. Georgia Inst. of Tech 14:40-15:00 MoA4.6 Process Parameter Optimization Based on LW-PLS in Pharmaceutical Granulation Process, pp Yoshizaki, Ryosuke Kyoto Univ 25 Kano, Manabu Tanabe, Shuichi Miyano, Takuya MoP2 Poster 1 (Poster Session) Chair: Scali, Claudio Kyoto Univ Daiichi Sankyo Co., Ltd Daiichi Sankyo Co., Ltd Garibaldi Univ. of Pisa Co-Chair: El-Farra, Nael H. Univ. of California, Davis 15:00-17:00 MoP2.1 Revision of the Tennessee Eastman Process Model, pp Bathelt, Andreas Cologne Univ. of Applied Sciences Ricker, N. Lawrence Univ. of Washington Jelali, Mohieddine Cologne Univ. of Applied Sciences 15:00-17:00 MoP2.2 Simulation and Control of Monomer Conversion in a Continuous Emulsion Polymerization Reactor, pp Barazandegan, Melissa Univ. of British Columbia Shahrokhi, Mohammad Sharif Univ. of Tech Abedini, Hossein Iranian Pol. and Petrochemical Inst Vafa, Ehsan Sharif Univ. of Tech 15:00-17:00 MoP2.3 Modeling and Simulation for Feasibility Study of Taylor- Couette Crystallizer As Crystal Seed Manufacturing System, pp Park, Kiho Korea Univ Yang, Dae Ryook Korea Univ 15:00-17:00 MoP2.4 Distributed MPC for Upstream Oil & Gas Fields - a Practical View, pp Al-Naumani, Yahya Hamood Univ. of Sheffield Rossiter, J. Anthony Univ. of Sheffield 15:00-17:00 MoP2.5 Box-Complex Assisted Genetic Algorithm for Optimal Control of Batch Reactor, pp Patel, Narendra Vishwakarma Government Engineering Coll. Chandkheda Padhiyar, Nitin Indian Inst. of Tech. Gandhinagar 15:00-17:00 MoP2.6 Global Optimization of an Industrial Natural Gas Production Network, pp Li, Dan Queen S Univ Li, Xiang Queen S Univ 15:00-17:00 MoP2.7 Predicting Electricity Pool Prices Using Hidden Markov Models, pp Wu, Ouyang Liu, Tianbo Huang, Biao Forbes, J. Fraser 15:00-17:00 MoP2.8 Optimal and Coordinated Functioning of Oil and Gas Wells, pp Bandi, Apeksha Mukhtyar, Vishwa A. Gudi, Ravindra Indian Inst. of Tech. Bombay Shell Tech. Center IIT Bombay

27 15:00-17:00 MoP2.9 Real Time Optimisation of Industrial Gas Supply Networks, pp Adamson, Richard Newcastle Univ Hobbs, Martin BOC Gases Ltd Silcock, Andy BOC Gases Ltd Montague, Gary Teesside Univ 15:00-17:00 MoP2.10 Identification and Control of Chemical Processes Using the Anisochronic Modeling Paradigm, pp Espinoza, Bolaños, Mauricio Univ. of Costa Rica Rojas, Jose David Univ. of Costa Rica Vilanova, Ramon Univ. Autònoma De Barcelona Arrieta, Orlando Univ. of Costa Rica 15:00-17:00 MoP2.11 Urea-SCR Process Control for Diesel Engine Using Feedforward-Feedback Nonlinear Method, pp Zhao, Jinghua Jilin Univ. Campus NanLing Chen, Zhigang Jilin Univ. Campus NanLing Hu, Yunfeng Jilin Univ. Campus NanLing Chen, Hong Jilin Univ. Campus NanLing 15:00-17:00 MoP2.12 Optimization of Catalytic Naphtha Reforming Process Based on Modified Differential Evolution Algorithm, pp Wei, Min East China Univ. of Science and Tech Yang, Minglei East China Univ. of Science and Tech Qian, Feng East China Univ. of Science and Tech Du, Wenli East China Univ. of Science and Tech 15:00-17:00 MoP2.13 Optimal Scheduling of the Maintenance and Improvement for Water Main System Using Markov Decision Process, pp Kim, Jong Woo Seoul National Univ Choi, Gobong Seoul National Univ Suh, Jung Chul Samchully Lee, Jong Min Seoul National Univ 15:00-17:00 MoP2.14 Energy Demand Response of Process Systems through Production Scheduling and Control, pp Tong, Chudong Univ. of California at Davis El-Farra, Nael H. Univ. of California at Davis Palazoglu, Ahmet N. Univ. of California at Davis 15:00-17:00 MoP2.15 Time and Frequency Performance Assessment of IMC PI Control Loops, pp Barroso, Henrique C. Univ. Federal De Campina Grande Acioli Junior, George Univ. Federal De Campina Grande Barros, Péricles R. Univ. Federal De Campina Grande 15:00-17:00 MoP2.16 A Novel and Efficient Hybrid Optimization Approach for Wind Farm Micro-Siting, pp Mittal, Prateek Kulkarni, Kedar Indian Inst. of Tech. Hyderabad ABB Corp. Res. Centre, Bangalore 26 Mitra, Kishalay IIT Hyderabad 15:00-17:00 MoP2.17 Inferential Active Disturbance Rejection Control of a Distillation Column, pp Al Kalbani, Fahad Newcastle Univ Zhang, Jie Newcastle Univ 15:00-17:00 MoP2.18 Decentralized SISO Active Disturbance Rejection Control of the Newell-Lee Forced Circulation Evaporator, pp Dittmar, Rainer West Coast Univ. of Applied Sciences 15:00-17:00 MoP2.19 Sulfur Determination in Diesel Using 2D Fluorescence Spectroscopy and Linear Models, pp Ranzan, Cassiano Federal Univ. of Rio Grande Do Sul Ranzan, Lucas Federal Univ. of Rio Grande Do Sul Trierweiler, Luciane Ferreira Federal Univ. of Rio Grande Do Sul Trierweiler, Jorge Otávio Federal Univ. of Rio Grande Do Sul 15:00-17:00 MoP2.20 Detection of Stiction in Level Control Loops, pp Brasio, Ana S R Univ. of Coimbra Romanenko, Andrey Ciengis, SA, Coimbra Fernandes, Natercia C.P. Univ. of Coimbra 15:00-17:00 MoP2.21 Soft Sensor Model Maintenance: A Case Study in Industrial Processes, pp Chen, Kuilin McMaster Univ Castillo, Ivan The Dow Chemical Company Chiang, Leo The Dow Chemical Company Yu, Jie McMaster Univ 15:00-17:00 MoP2.22 A New Implementation of Open-Loop Two-Move Compensation Method for Oscillations Caused by Control Valve Stiction, pp Wang, Tingren Zhejiang Univ Xie, Lei Zhejiang Univ Tan, Feiqi Zhejiang Univ Su, Hongye Zhejiang Univ 15:00-17:00 MoP2.23 Dumpling Cooking - Modeling and Simulation, pp Zhu, Qiang Zhejiang Univ Liang, Yuan Zhejiang Univ Shao, Zhijiang Zhejiang Univ 15:00-17:00 MoP2.24 Reducing Fuel Cell Degradation in Micro Combined Heat and Power Systems, pp Zenith, Federico Sintef 15:00-17:00 MoP2.25 Monitoring Safety of Process Operations Using Industrial Workflows, pp Dasani, Sridhar Shah, Sirish L. Chen, Tongwen Funnell, Jay Pollard, Robert W.

28 15:00-17:00 MoP2.26 Multi-Innovation Parameter Estimation for Hammerstein MIMO Output-Error Systems Based on the Key-Term Separation, pp Shen, Qianyan Jiangnan Univ Ding, Feng Jiangnan Univ 15:00-17:00 MoP2.27 Multivariate Data Analysis of Gas-Metal Arc Welding Process, pp Ranjan, Rajesh IIIT Roorkee Talati, Anurag Ho, Megan Univ. of British Columbia, Vancouver, BC Bharmal, Hussain IIT Bombay Bavdekar, Vinay Prasad, Vinay Mendez, Patricio 15:00-17:00 MoP2.28 Industrial Test Setup for Autotuning of PID Controllers in Large-Scale Processes: Applied to Tennessee Eastman Process, pp Jahanshahi, Esmaeil Siemens AS Sivalingam, Selvanathan Siemens AS Schofield, Brad Lund Univ 15:00-17:00 MoP2.29 Control-Relevant Multiple Linear Modeling of Simulated Moving Bed Chromatography, pp Sharma, Girish IIT Bombay Vignesh, S V IIT Bombay Hariprasad, K IIT Bombay Bhartiya, Sharad IIT Bombay 15:00-17:00 MoP2.30 Pseudo-LIDAR Data Analysis and Feed-Forward Wind Turbine Control Design, pp Bao, Jie Univ. of Strathclyde Wang, Mengling Univ. of Strathclyde Yue, Hong Univ. of Strathclyde Leithead, William Univ. of Strathclyde 15:00-17:00 MoP2.31 Adaptive Optimizing Control of an Ideal Reactive Distillation Column, pp Valluru, Jayaram IIT Bombay Purohit, Jalesh IIT Bombay Patwardhan, Sachin C. IIT Bombay Mahajani, Sanjay IIT Bombay 15:00-17:00 MoP2.32 Design and Implementation of a Multiple-Model Based Control Scheme for Boiler-Turbine Unit, pp Siam Sundar, Kapil Arasu Madras Inst. of Tech Prakash, Jagadeesan Madras Inst. of Tech 15:00-17:00 MoP2.33 Analytical Scheme of Centralized PI Controller for Non- Square Processes with Time-Delays, pp Wang, Zhiqiang Luan, Xiaoli Liu, Fei MoRT1 Roundtable Discussion (Panel Discussion) Jiangnan Univ Jiangnan Univ Jiangnan Univ 27 Chair: Guay, Martin Queen s Univ. Co-Chair: Shah, Sirish L. 15:40-17:00 MoRT1.1 Industrial Challenges and Opportunities for Research in Process Control and Monitoring*. Lee, Jay H. Bonvin, Dominique Espejo, Aris Backstrom, Johan Chmelyk, Terrance Cott, Barry Bartusiak, Donald Bill Poe, William A. MoKA1 Keynote 3 (Keynote Session) Chair: Monnigmann, Martin Kaist Epfl Syncrude Canada Ltd Honeywell Measurex Inc Spartan Controls Shell Global Solutions International BV ExxonMobil Res. & Engineering Schneider Electric Ruhr-Univ. Bochum Co-Chair: Allgower, Frank Univ. of Stuttgart 17:00-17:30 MoKA1.1 Economic Optimization of Spray Dryer Operation Using Nonlinear Model Predictive Control with State Estimation, pp Petersen, Lars Norbert Jørgensen, John B. Rawlings, James B. MoKA2 Keynote 4 (Keynote Session) Chair: Kano, Manabu Tech. Univ. of Denmark Tech. Univ. of Denmark Univ. of Wisconsin at Madison Spearhead Kyoto Univ. Co-Chair: Perrier, Michel Ec. Pol. 17:00-17:30 MoKA2.1 A Stable Two-Time Dimensional (2D) Model Predictive Control with Zero Terminal State Constraints for Constrained Batch Processes, pp Lu, Jingyi Cao, Zhixing Gao, Furong TuPLP Tuesday June 9, 2015 Plenary 2 (Plenary Session) Chair: Guay, Martin Hong Kong Univ. of Sci. & Tech Hong Kong Univ. of Sci. & Tech Hong Kong Univ. of Sci. & Tech Queen's Univ. Co-Chair: Shah, Sirish L. 08:30-09:30 TuPLP.1 Process Data Analytics Via Latent Structure Modeling, pp Qin, S. Joe TuKM1 Keynote 5 (Keynote Session) Chair: Scali, Claudio Univ. of Southern California Univ. of Pisa Co-Chair: Shah, Sirish L. 09:30-10:00 TuKM1.1 Latent Variable Models and Big Data in the Process Industries, pp

29 Macgregor, John F. Bruwer, Mark-John Miletic, Ivan Cardin, Marlene Liu, Zheng TuKM2 Keynote 6 (Keynote Session) Chair: Monnigmann, Martin ProSensus, Inc ProSensus, Inc ProSensus, Inc ProSensus, Inc ProSensus, Inc Spearhead Ruhr-Univ. Bochum Co-Chair: Chen, Hong Jilin Univ. Campus NanLing 09:30-10:00 TuKM2.1 On the Design of Economic NMPC Based on an Exact Turnpike Property, pp Faulwasser, Timm Bonvin, Dominique TuM1 Predictive Control Applications (Regular Session) Chair: Patwardhan, Sachin C. Epfl Epfl Indian Inst. of Tech. Bombay Co-Chair: Gates, Ian Univ. of Calgary 10:20-10:40 TuM1.1 Model Predictive Control in Industry: Challenges and Opportunities, pp Forbes, Michael Gregory Honeywell Patwardhan, Rohit Saudi Aramco Hamadah, Hamza Saudi Aramco Gopaluni, Bhushan Univ. of British Columbia 10:40-11:00 TuM1.2 Model-Predictive-Control (MPC) of Steam Trap Subcool in Steam-Assisted Gravity Drainage (SAGD), pp Purkayastha, Sagar Neel Univ. of Calgary Gates, Ian Univ. of Calgary Trifkovic, Milana Univ. of Calgary 11:00-11:20 TuM1.3 Experimental Evaluation of a MIMO Adaptive Dual MPC, pp Kumar, Kunal IIT Bombay Heirung, Tor Aksel N. Norwegian Univ. of Science & Tech Patwardhan, Sachin C. Indian Inst. of Tech. Bombay Foss, Bjarne Norwegian Univ. of Science & Tech 11:20-11:40 TuM1.4 Distributed Model Predictive Control Based on Nash Optimality for Large Scale Irrigation Systems, pp Zhang, Rongchao Zhejiang Univ. of Tech Liu, Andong Zhejiang Univ. of Tech Yu, Li Zhejiang Univ. of Tech Zhang, Wen-An Zhejiang Univ. of Tech 11:40-12:00 TuM1.5 Optimizing Control of a Tubular Polymerization Reactor: Comparison of Single Shooting and Full Discretization, pp Hashemi, Reza TU Dortmund Schilling, Ricardo TU Dortmund Engell, Sebastian TU Dortmund 12:00-12:20 TuM1.6 A Model Predictive Controller for Inverse Response Control Systems, pp Vu, Ky TuM2 Energy Processes and Control I (Regular Session) Chair: El-Farra, Nael H. Co-Chair: Daoutidis, Prodromos AuLac Tech. Inc Spearhead Univ. of California, Davis Univ. of Minnesota 10:20-10:40 TuM2.1 Modeling and Control of Rankine Based Waste Heat Recovery Systems for Heavy Duty Trucks, pp Grelet, Vincent Volvo Trucks Dufour, Pascal Univ. Lyon 1 - CNRS Nadri, Madiha Univ. Claude Bernard Lyon 1 Reiche, Thomas Volvo Trucks Lemort, Vincent Univ. of Liège 10:40-11:00 TuM2.2 Wiener Model and Extremum Seeking Control for a CO Preferential Oxidation Reactor with the CuO-CeO2 Catalyst, pp Lee, Hyun Chan Kyungpook National Univ Kim, Sin Kyungpook National Univ Heo, Jae Pil Kyungpook National Univ Kim, Dong Hyun Kyungpook National Univ Lee, Jietae Kyungpook National Univ 11:00-11:20 TuM2.3 Control of a Post-Combustion CO2 Capture Plant During Process Start-Up and Load Variations, pp Gaspar, Jozsef Tech. Univ. of Denmark Jørgensen, John B. Tech. Univ. of Denmark Fosbøl, Philip Loldrup Tech. Univ. of Denmark 11:20-11:40 TuM2.4 Graph Reduction for Material Integrated Process Networks with Flow Segregation, pp Heo, Seongmin Univ. of Minnesota Daoutidis, Prodromos Univ. of Minnesota 11:40-12:00 TuM2.5 Proactive Optimization and Control of Heat-Exchanger Super Networks, pp Wang, Xiaonan Univ. of California at Davis Palazoglu, Ahmet N. Univ. of California at Davis El-Farra, Nael H. Univ. of California at Davis 12:00-12:20 TuM2.6 Operational Optimization of SWRO Process with the Consideration of Load Fluctuation and Electricity Price, pp Jiang, Aipeng Jiangzhou, Shu Cheng, Wen Wang, Jian Ding, Qiang Xing, Changxin TuM3 Process and Control Monitoring I (Regular Session) Chair: de Prada, Cesar Co-Chair: Pannocchia, Gabriele Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Wedgemount Univ. of Valladolid Univ. of Pisa 10:20-10:40 TuM3.1 28

30 Kernel Canonical Variate Analysis for Nonlinear Dynamic Process Monitoring, pp Samuel, Raphael T. Cranfield Univ Cao, Yi Cranfield Univ 10:40-11:00 TuM3.2 A Nonlinear Quality-Relevant Process Monitoring Method with Kernel Input-Output Canonical Variate Analysis, pp Huang, Linzhe China Univ. of Petroleum Cao, Yuping China Univ. of Petroleum Tian, Xuemin China Univ. of Petroleum Deng, Xiaogang China Univ. of Petroleum 11:00-11:20 TuM3.3 Robust Process Monitoring Via Stable Principal Component Pursuit, pp Chen, Chun-Yu National Tsing Hua Univ Yao, Yuan National Tsing Hua Univ 11:20-11:40 TuM3.4 Gross Error Management in Data Reconciliation, pp De La Fuente, Maria Jesus Univ. of Valladolid Gutierrez, Gloria Univ. of Valladolid Gomez Sayalero, Elena Univ. of Valladolid Sarabia, Daniel Univ. of Burgos de Prada, Cesar Univ. of Valladolid 11:40-12:00 TuM3.5 Identification Techniques for Stiction Quantification in the Presence of Nonstationary Disturbances, pp Bacci di Capaci, Riccardo Univ. of Pisa Scali, Claudio Univ. of Pisa Pannocchia, Gabriele Univ. of Pisa 12:00-12:20 TuM3.6 Stiction Quantification Based on Time and Frequency Domain Criterions, pp TuM4 Li, Chen Qian, Feng Choudhury, M.A.A. Shoukat Du, Wenli East China Univ. of Science and Tech East China Univ. of Science and Tech Bangladesh Univ. of Engineering Tech East China Univ. of Science and Tech Alarm Systems Design and Monitoring (Invited Session) Chair: Shah, Sirish L. Black Tusk Co-Chair: Chen, Tongwen 10:20-10:40 TuM4.1 An Application of Advanced Alarm Management Tools to an Oil Sand Extraction Plant (I), pp Hu, Wenkai Afzal, Muhammad Shahzad Brandt, Gustavo Suncor Energy Inc Lau, Eric Suncor Energy Inc Chen, Tongwen Shah, Sirish L. 10:40-11:00 TuM4.2 Fast Sequence Alignment for Comparing Industrial Alarm Floods (I), pp Hu, Wenkai Wang, Jiandong Peking Univ Chen, Tongwen 11:00-11:20 TuM4.3 Mode Based Alarm Solutions at Syncrude Canada (I), pp Bhaumik, Suvomoy Syncrude Canada Ltd MacGowan, John Syncrude Canada Ltd Doraj, Vimal Syncrude Canada Ltd 11:20-11:40 TuM4.4 Methodology and Application of Pattern Mining in Multiple Alarm Flood Sequences (I), pp Lai, Shiqi Chen, Tongwen 11:40-12:00 TuM4.5 Risk-Based Warning System Design Methodology for Multimode Processes (I), pp Wang, Hangzhou Memorial Univ Khan, Faisal I Memorial Univ Ahmed, Salim Memorial Univ Imtiaz, Syed Memorial Univ 12:00-12:20 TuM4.6 Design and Analysis of Improved Alarm Delay-Timers (I), pp Zang, Hao Yang, Fan Huang, Dexian TuA1 Tsinghua Univ Tsinghua Univ Tsinghua Univ Extremum Seeking and Adaptive Control (Regular Session) Chair: Guay, Martin Queen's Univ. Co-Chair: Bao, Jie The Univ. of New South Wales 13:30-13:50 TuA1.1 Proportional-Integral Extremum-Seeking Control, pp Guay, Martin Queen S Univ 13:50-14:10 TuA1.2 Adaptive Control of Chemical Distributed Parameter Systems, pp Babaei Pourkargar, Davood The Pennsylvania State Univ Armaou, Antonios The Pennsylvania State Univ 14:10-14:30 TuA1.3 High-Order Differential Dissipativity Analysis of Nonlinear Processes, pp Wang, Ruigang The Univ. of New South Wales Tippett, Michael James The Univ. of New South Wales Bao, Jie The Univ. of New South Wales 14:30-14:50 TuA1.4 Distributed Extremum-Seeking Control Over Networks of Unstable Dynamic Agents, pp Guay, Martin Queen S Univ Vandermeulen, Isaac Queen S Univ Dougherty, Sean CALM Tech. Inc McLellan, P. James Queen S Univ 14:50-15:10 TuA1.5 Neighbouring-Extremal Control for Steady-State Optimization Using Noisy Measurements, pp de Oliveira, Vinicius Jäschke, Johannes Norwegian Univ. of Science & Tech Norwegian Univ. of Science & 29

31 Tech Skogestad, Sigurd Norwegian Univ. of Science & Tech 15:10-15:30 TuA1.6 Dissipativity-Based Analysis of Controller Networks with Reduced Rate Communication, pp Tippett, Michael James Zheng, Chaoxu Bao, Jie Liu, Jinfeng TuA2 The Univ. of New South Wales The Univ. of New South Wales The Univ. of New South Wales Energy Processes and Control II (Regular Session) Chair: Monnigmann, Martin Co-Chair: Monder, Dayadeep Singh Spearhead Ruhr-Univ. Bochum Indian Inst. of Tech. Bombay 13:30-13:50 TuA2.1 Model Predictive Control of the Steam Cycle in a Solar Power Plant, pp Mier, Dominik Ruhr-Univ. Bochum Möllenbruck, Florian Ruhr-Univ. Bochum Jost, Michael Ruhr-Univ. Bochum Grote, Wolfgang MAN Diesel & Turbo SE Monnigmann, Martin Ruhr-Univ. Bochum 13:50-14:10 TuA2.2 Model Predictive Control of Once through Steam Generator Steam Quality, pp Qi, Fei Suncor Energy Inc Shukeir, Eliyya Suncor Energy Inc Kadali, Ramesh Suncor Energy Inc 14:10-14:30 TuA2.3 Optimal Concentration Control for Direct Methanol Fuel Cells, pp Zenith, Federico Sintef Na, Youngseung TU Braunschweig Krewer, Ulrike TU Braunschweig 14:30-14:50 TuA2.4 Nonlinear Operability of a Membrane Reactor for Direct Methane Aromatization, pp Carrasco, Juan C. West Virginia Univ Lima, Fernando V. West Virginia Univ 14:50-15:10 TuA2.5 A Distributed Parameter Model for a Solid Oxide Fuel Cell: Simulating Realistic Operating Conditions, pp Monder, Dayadeep Singh IIT Bombay Polisetty, Venkata Goutham IIT Hyderabad Jampana, Phanindra IIT Hyderabad Janardhanan, Vinod M. IIT Hyderabad 15:10-15:30 TuA2.6 Dynamic Operational Optimization of Air Source Heat Pump Heating System with the Consideration of Energy Saving, pp Xing, Chang Xin Ding, Qiang Jiang, Aipeng Cheng, Wen Zhou, Dahan Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Hangzhou Dianzi Univ Process and Control Monitoring II (Regular Session) Chair: Gopaluni, Bhushan Univ. of British Columbia Co-Chair: Qin, S. Joe Univ. of Southern California 13:30-13:50 TuA3.1 A Novel Algorithm for Model-Plant Mismatch Detection for Model Predictive Controllers, pp Tsai, Yiting Univ. of British Columbia Gopaluni, Bhushan Univ. of British Columbia Marshman, Devin James Univ. of British Columbia Chmelyk, Terrance NORPAC Controls 13:50-14:10 TuA3.2 Assessment of Model-Plant Mismatch by the Nominal Sensitivity Function for Unconstrained MPC, pp Botelho, Viviane Rodrigues Federal Univ. of Rio Grande Do Sul Trierweiler, Jorge Otávio Federal Univ. of Rio Grande Do Sul Farenzena, Marcelo Federal Univ. of Rio Grande Do Sul Duraiski, Ricardo Trisolutions Engineering Solutions LTDA 14:10-14:30 TuA3.3 Drill-Down Diagnosis of Deficient Models in MPC, pp Li, Lijuan Nanjing Tech. Univ Qin, S. Joe Univ. of Southern California 14:30-14:50 TuA3.4 A Method for Automatic Detection of Controller Tuning Issues, pp Ghosh, Kaushik ABB Corp. Res. Centre, Bangalore Nallasivam, Ulaganathan Purdue Univ Kubal, Nandkishor Abb 14:50-15:10 TuA3.5 Multirate Partial Least Squares for Process Monitoring, pp Cong, Ya Zhejiang Univ Ge, Zhiqiang Zhejiang Univ Song, Zhi-Huan Zhejiang Univ 15:10-15:30 TuA3.6 PLS-Based Similarity Analysis for Mode Identification in Multimode Manufacturing Processes, pp TuP2 Zheng, Ying Qin, S. Joe Wang, Fuli Poster 2 (Poster Session) Chair: Gudi, Ravindra Co-Chair: Jørgensen, John B. Huazhong Univ. of Science and Tech Univ. of Southern California and Chinese Univ. of Hong Northeastern Univ Garibaldi IIT Bombay 2-control ApS 15:30-17:00 TuP2.1 Parametric Identifier of Metabolic Networks Based on Robust Differentiation, pp Sepúlveda-Gálvez, Alfonso Badillo-Corona, Agustín Chairez, Isaac Upibi-Ipn Upibi-Ipn Cinvestav-Ipn TuA3 Wedgemount 30 15:30-17:00 TuP2.2

32 Parameter Estimation for Non-Uniformly Sampled Wiener Systems with Dead-Zone Nonlinearities, pp Liu, Ranran Jiangsu Univ Li, Haoran Jiangsu Univ Pan, Tianhong Jiangsu Univ Li, Zhengming Jiangsu Univ 15:30-17:00 TuP2.3 Identification of Equation Error Models from Small Samples Using Compressed Sensing Techniques, pp Perepu, Satheesh Kumar IIT Madras Tangirala, Arun K. IIT Madras 15:30-17:00 TuP2.4 Soft-Sensing in Complex Chemical Process Based on a Sample Clustering Extreme Learning Machine Model, pp Peng, Di Beijing Univ. of Chemical Tech Xu, Yuan Beijing Univ. of Chemical Tech Wang, Yanqing Beijing Univ. of Chemical Tech Geng, Zhiqiang Beijing Univ. of Chemical Tech Zhu, Qunxiong Beijing Univ. of Chemical Tech 15:30-17:00 TuP2.5 A MPC Operation Method for a Photovoltaic System with Batteries, pp Liu, Bing Hong Kong Univ. of Sci. & Tech Lu, Zhou Hong Kong Univ. of Sci. & Tech Yao, Ke Hong Kong Univ. of Sci. & Tech Gao, Furong Hong Kong Univ. of Sci. & Tech 15:30-17:00 TuP2.6 A Survey of Guaranteeing Feasibility and Stability in MPC During Target Changes, pp Dughman, Shukri Univ. of Sheffield Rossiter, J. Anthony Univ. of Sheffield 15:30-17:00 TuP2.7 Cascade Nonlinear Control for a Class of Cascade Systems, pp Garcia-Sandoval, Juan Paulo Univ. of Guadalajara Dochain, Denis Univ. Catholique De Louvain Gonzalez-Alvarez, Victor Univ. of Guadalajara 15:30-17:00 TuP2.8 Modeling of Bisphenol a Condensation Reaction Based on UKF Algorithm, pp Cang, Wentao Jiangnan Univ Xie, Li Jiangnan Univ Yang, Huizhong Jiangnan Univ 15:30-17:00 TuP2.9 N-Step Impacted-Region Optimization Based Distributed Model Predictive Control, pp Zheng, Yi Shanghai Jiao Tong Univ Li, Shaoyuan Shanghai Jiao Tong Univ 15:30-17:00 TuP2.10 A Multi-Model Identification Method for the Fiber Stretching Process Based on the EM Algorithm, pp Guo, Fan Donghua Univ Ding, Yongsheng Donghua Univ Chen, Lei Donghua Univ Ren, Lihong Donghua Univ Hao, Kuangrong Donghua Univ 15:30-17:00 TuP2.11 Integrating Iterative Learning Estimation with Optimal Control for Batch Productivity Enhancement, pp Gupta, Anish Indian Inst. of Tech. Bombay Gudi, Ravindra IIT Bombay 15:30-17:00 TuP2.12 Data Filtering Based Parameter Estimation Algorithms for Multivariable Box-Jenkins-Like Systems, pp Wang, Yanjiao Jiangnan Univ Xu, Ling Jiangnan Univ Ding, Feng Jiangnan Univ 15:30-17:00 TuP2.13 Multi-Innovation Gradient Identification for Input Nonlinear State Space Systems, pp Wang, Xuehai Jiangnan Univ Liu, Yanjun Jiangnan Univ Ding, Feng Jiangnan Univ 15:30-17:00 TuP2.14 Simultaneous Control Loop Performance Assessment and Process Identification Based on Fractional Models, pp Skarda, Radek Univ. of West Bohemia Cech, Martin Univ. of West Bohemia Schlegel, Milos Univ. of West Bohemia in Pilsen 15:30-17:00 TuP2.15 Fractional-Order Process Simulator Based on Exact Step Response Discretization, pp Cech, Martin Univ. of West Bohemia Schlegel, Milos Univ. of West Bohemia Reitinger, Jan Univ. of West Bohemia 15:30-17:00 TuP2.16 Model-Based Fault-Tolerant Control of Uncertain Particulate Processes: Integrating Fault Detection, Estimation and Accommodation, pp Napasindayao, Trina Univ. of California, Davis El-Farra, Nael H. Univ. of California, Davis 15:30-17:00 TuP2.17 Reliable H Control of Switched Linear Systems, pp Fu, Jun Northeastern Univ Chai, Tianyou Northeastern Univ Jin, Ying McGill Univ Ma, Ruicheng Liaoning Univ. China 15:30-17:00 TuP2.18 An Observer-Based Model Predictive Control Strategy for Distributed Parameter System, pp Wang, Mengling East China Univ. of Science and Tech Shi, Hongbo East China Univ. of Science and Tech Yang, Wen East China Univ. of Science and Tech 15:30-17:00 TuP2.19 Iterative Identification of Output Error Model with Time Delay, pp Dong, Shijian Dalian Univ. of Tech Liu, Tao Dalian Univ. of Tech Chen, Fengwei Univ. of Lorraine 15:30-17:00 TuP2.20 Integration of Design and Control Using Efficient PSE Approximations, pp

33 Bahakim, Sami Saeed Mehta, Siddharth Ahmad, Hassan Gaspar, Erik Ricardez-Sandoval, Luis Alberto Univ. of Waterloo Univ. of Waterloo Univ. of Waterloo Univ. of Waterloo Univ. of Waterloo 15:30-17:00 TuP2.21 Development of an Ant Colony Optimization (ACO) Algorithm Based on Statistical Analysis and Hypothesis Testing for Variable Selection, pp Pessoa, Carolina de Marco Federal Univ. of Rio Grande Do Sul Ranzan, Cassiano Federal Univ. of Rio Grande Do Sul Trierweiler, Luciane Ferreira Federal Univ. of Rio Grande Do Sul Trierweiler, Jorge Otávio Federal Univ. of Rio Grande Do Sul 15:30-17:00 TuP2.22 A Bilevel Programming Formulation for Dynamic Real- Time Optimization, pp Jamaludin, Mohammad McMaster Univ Zamry Swartz, Christopher L.E. McMaster Univ 15:30-17:00 TuP2.23 Handling Parametric Drift in Batch Crystallization Using Predictive Control with R2R Model Parameter Estimation, pp Kwon, Joseph Ucla Nayhouse, Michael Ucla Ni, Dong Zhejiang Univ Christofides, Panagiotis D. Univ. of California at Los Angeles 15:30-17:00 TuP2.24 Algorithm for Image-Based Biomarker Detection for Differential Diagnosis of Parkinson's Disease, pp Singh, Gurpreet Samavedham, Lakshminarayanan National Univ. of Singapore National Univ. of Singapore 15:30-17:00 TuP2.25 Double-Objective Optimal Control for Non-Gaussian Systems: An Example Study on Analytical vs Numerical Solutions, pp Ren, Mifeng Taiyuan Univ. of Tech Zhang, Jianhua North China Electric Power Univ Wang, Hong Univ. of Manchester Huang, Min Northeastern Univ 15:30-17:00 TuP2.26 Robust Nonlinear Predictive Control for a Bioreactor Based on a Dynamic Metabolic Flux Balance Model, pp Kumar, Divya Univ. of Waterloo Budman, Hector M. Univ. of Waterloo 15:30-17:00 TuP2.27 Fast Mesh-Sorting in Multi-Objective Optimization, pp Patel, Narendra Vishwakarma Government Engineering Coll. Chandkheda Padhiyar, Nitin Indian Inst. of Tech. Gandhinagar 15:30-17:00 TuP2.28 Parameter and Delay Estimation of Fractional Order Models from Step Response, pp Ahmed, Salim Memorial Univ 15:30-17:00 TuP2.29 Asynchronous Separable Self-Triggered Model Predictive Control Based on Relaxed Dynamic Programming, pp Lu, Liang Northeastern Univ. and KAIST 15:30-17:00 TuP2.30 Unraveling Apoptosis Signalling Using Linear Control Methods: Linking the Loop Gain to Reverting the Decision to Undergo Apoptosis, pp Schliemann-Bullinger, Monica Readman, Mark C. Kalamatianos, Dimitrios Findeisen, Rolf Bullinger, Eric Otto-Von-Guericke Univ. Magdeburg Stockport Coll Biomedical Res. Foundation of the Acad. of Athens Otto-Von-Guericke-Univ. Magdeburg Otto-Von-Guericke-Univ. Magdeburg 15:30-17:00 TuP2.31 Overload Detection in Semi-Autogenous Grinding: A Nonlinear Process Monitoring Approach, pp McClure, Ken Gopaluni, Bhushan TuKA1 Keynote 7 (Keynote Session) Chair: Kano, Manabu Spartan Controls Ltd Univ. of British Columbia Kyoto Univ. Co-Chair: Mhaskar, Prashant McMaster Univ. 17:00-17:30 TuKA1.1 Analysis of Problems Induced by Imprecise Dating of Measurements in Oil and Gas Production, pp Petit, Nicolas TuKA2 Keynote 8 (Keynote Session) Chair: Findeisen, Rolf MINES ParisTech Spearhead Otto-von-Guericke-Univ. Magdeburg Co-Chair: Mesbah, Ali Univ. of California, Berkeley 17:00-17:30 TuKA2.1 A Multiobjective Optimization Perspective on the Stability of Economic MPC, pp Zavala, Victor M. WePLP Wednesday June 10, 2015 Plenary 3 (Plenary Session) Chair: Findeisen, Rolf Argonne National Lab Otto-von-Guericke-Univ. Magdeburg Co-Chair: Gopaluni, Bhushan Univ. of British Columbia 08:30-09:30 WePLP.1 Set-Theoretic Approaches in Analysis, Estimation and Control of Nonlinear Systems, pp Chachuat, Benoit Houska, Boris Imperial Coll. London ShanghaiTech Univ

34 Paulen, Radoslav Perić, Nikola Rajyaguru, Jai Villanueva, Mario E. WeKM1 Keynote 9 (Keynote Session) Chair: Prasad, Vinay Tech. Univ. Dortmund Imperial Coll. London Imperial Coll. London Imperial Coll. London Co-Chair: Findeisen, Rolf Otto-von-Guericke-Univ. Magdeburg 09:30-10:00 WeKM1.1 Control Challenges in Synthetic Biology, pp Rao, Christopher V. Univ. of Illinois at Urbana- Champaign Dual MPC for FIR Systems: Information Anticipation, pp Heirung, Tor Aksel N. Norwegian Univ. of Science & Tech Ydstie, B. Erik Carnegie Mellon Foss, Bjarne Norwegian Univ. of Science & Tech 12:00-12:20 WeM1.6 Stable Adaptive Predictive Control System Design Via Adaptive Output Predictor for Multi-Rate Sampled Systems, pp Mizumoto, Ikuro Ikejiri, Masataka Takagi, Taro Kumamoto Univ Kumamoto Univ National Inst. of Tech. Maizuru Coll WeKM2 Keynote 10 (Keynote Session) Chair: Gudi, Ravindra Spearhead IIT Bombay Co-Chair: McAuley, K.B. Queen's Univ. 09:30-10:00 WeKM2.1 Zone Model Predictive Control and Moving Horizon Estimation for the Regulation of Blood Glucose in Critical Care Patients, pp Knab, Timothy Clermont, Gilles Parker, Robert S. WeM1 Robust Predictive Control (Regular Session) Chair: Biegler, Lorenz T. Univ. of Pittsburgh Univ. of Pittsburgh Univ. of Pittsburgh Carnegie Mellon Univ. Co-Chair: Lucia, Sergio OvG Univ. of Magdeburg 10:20-10:40 WeM1.1 Robust Output Feedback Model Predictive Control Using Reduced Order Models, pp Koegel, Markus J. Otto-Von-Guericke Univ. Magdeburg Findeisen, Rolf Otto-Von-Guericke Univ. Magdeburg 10:40-11:00 WeM1.2 Potential and Limitations of Multi-Stage Nonlinear Model Predictive Control, pp Lucia, Sergio Otto-Von-Guericke Univ. Magdeburg Engell, Sebastian TU Dortmund 11:00-11:20 WeM1.3 User Friendly Robust MPC Tuning of Uncertain Paper- Making Processes, pp He, Ning Shi, Dawei Beijing Inst. of Tech Wang, Jiadong Forbes, Michael Gregory Honeywell Backstrom, Johan Honeywell Measurex Inc Chen, Tongwen 11:20-11:40 WeM1.4 Trajectory Bounds of Input-To-State Stability for Nonlinear Model Predictive Control, pp Griffith, Devin Carnegie Mellon Univ Biegler, Lorenz T. Carnegie Mellon Univ 11:40-12:00 WeM WeM2 Thermodynamics and Process Control (Invited Session) Chair: Dochain, Denis Co-Chair: Couenne, Francoise Spearhead Univ. Catholique de Louvain Univ. of Lyon 1 10:20-10:40 WeM2.1 Lyapunov Based Nonlinear Control of Tubular Chemical Reactors (I), pp Zhou, Weijun Univ. Claude Bernard Lyon 1 Hamroun, Boussad Lab. D'automatique Et Génie Des Procédés Le Gorrec, Yann Femto-St, Ensmm Couenne, Francoise Univ. of Lyon 1 10:40-11:00 WeM2.2 On the Relaxing Dissipation of Dissipative Pseudo Hamiltonian Models (I), pp Hoang, Ngoc Ha Univ. of Tech. VNU-HC Phong Mai, T. Univ. of Tech. VNU-HC Dochain, Denis Univ. Catholique De Louvain 11:00-11:20 WeM2.3 Dissipative and Conservative Structures for Thermo- Mechanical Systems (I), pp Garcia-Sandoval, Juan Paulo Univ. of Guadalajara Dochain, Denis Univ. Catholique De Louvain Hudon, Nicolas Univ. Catholique De Louvain 11:20-11:40 WeM2.4 Potential-Based Analysis of Closed Reacting Systems (I), pp Hudon, Nicolas Univ. Catholique De Louvain Dochain, Denis Univ. Catholique De Louvain Hoang, Ngoc Ha Univ. of Tech. (VNU-HCM) & Univ. Cath. De Louvain (Belgium) Garcia-Sandoval, Juan Paulo Univ. of Guadalajara 11:40-12:00 WeM2.5 Representation of Irreversible Systems in a Metric Thermodynamic Phase Space (I), pp Hudon, Nicolas Univ. Catholique De Louvain Dochain, Denis Univ. Catholique De Louvain Guay, Martin Queen S Univ 12:00-12:20 WeM2.6 Feedforward Ouput-Feedback Control for a Class of Exothermic Tubular Reactors, pp Najera, Isrrael Univ. Autónoma Metropolitana- Iztapalapa

35 Alvarez, Jesus Baratti, Roberto WeM3 Biological Systems (Regular Session) Chair: King, Rudibert Co-Chair: Vande Wouwer, Alain Univ. Autónoma Metropolitana Univ. Degli Studi Di Cagliari Wedgemount Tech. Univ. Berlin Univ. de Mons 10:20-10:40 WeM3.1 An Observer-Based Robust Control Strategy for Overflow Metabolism Cultures in Fed-Batch Bioreactors, pp Araujo Pimentel, Guilherme Univ. De Mons Benavides, Micaela Univ. De Mons Dewasme, Laurent Univ. De Mons Coutinho, Daniel Univ. Federal De Santa Catarina Vande Wouwer, Alain Univ. De Mons 10:40-11:00 WeM3.2 Adaptive Control of Lactic Acid Production Process from Wheat Flour, pp Gonzalez, Karen Vanessa CentraleSupelec Tebbani, Sihem Supelec Dumur, Didier CentraleSupelec Lopes, Filipa Ec. Centrale Paris Pareau, Dominique Ec. Centrale Paris Thorigné, Aurore Soufflet Givry, Sebastien Soufflet 11:00-11:20 WeM3.3 Dynamic Optimization of Biomass Productivity in Continuous Cultures of Microalgae Isochrysis Galbana through Modulation of the Light Intensity, pp Deschênes, Jean-Sébastien Univ. Du Québec à Rimouski Vande Wouwer, Alain Univ. De Mons 11:20-11:40 WeM3.4 Model-Based Control to Maximise Biomass and PHB in the Autotrophic Cultivation of Ralstonia Eutropha, pp Neddermeyer, Flavia Tech. Univ. Berlin Rossner, Niko Tech. Univ. Berlin King, Rudibert Tech. Univ. Berlin 11:40-12:00 WeM3.5 Extended and Unscented Kalman Filter Design for Hybridoma Cell Fed-Batch and Continuous Cultures, pp Fernandes, Sofia Univ. De Mons Richelle, Anne Univ. Libre De Bruxelles Amribt, Zakaria Univ. Libre De Bruxelles Dewasme, Laurent Univ. De Mons Bogaerts, Philippe Univ. Libre De Bruxelles Vande Wouwer, Alain Univ. De Mons 12:00-12:20 WeM3.6 Oscillatory Behavior Control in Continuous Fermentation Processes, pp Skupin, Piotr Metzger, Mieczyslaw WeM4 Process Applications (Regular Session) Chair: Prandini, Maria Silesian Univ. of Tech Silesian Univ. of Tech Black Tusk Pol. di Milano Co-Chair: Alvarez, Jesus Univ. Autonoma Metropolitana 10:20-10:40 WeM4.1 Integrated Process Design and Control of Reactive Distillation Processes, pp Mansouri, Seyed Soheil Tech. Univ. of Denmark Sales Cruz, Mauricio Univ. Autonoma Metropolitana- Cuajimalpa Huusom, Jakob Kjøbsted Tech. Univ. of Denmark Woodley, John M. Tech. Univ. of Denmak Gani, Rafiqul Tech. Univ. of Denmark 10:40-11:00 WeM4.2 Worst-Case and Distributional Robustness Analysis of a Thin Film Deposition Process, pp Rasoulian, Shabnam Ricardez-Sandoval, Luis Alberto Univ. of Waterloo Univ. of Waterloo 11:00-11:20 WeM4.3 Establishing Multivariate Specification Regions for Raw Materials Using SMB-PLS, pp Azari Dorcheh, Kamran Univ. Laval Lauzon-Gauthier, Julien Univ. Laval Tessier, Jayson Alcoa Smelting Center of Excellence Duchesne, Carl Univ. Laval 11:20-11:40 WeM4.4 Energy Saving through Control in an Industrial Multicomponent Distillation Column, pp Porru, Marcella Univ. Degli Studi Di Cagliari Baratti, Roberto Univ. Degli Studi Di Cagliari Alvarez, Jesus Univ. Autonoma Metropolitana 11:40-12:00 WeM4.5 An Intelligent Control Strategy for the Intervals of Temperature in a Plate Heat Exchanger, pp Jia, Yao State Key Lab. of Synthetical Automation for Process Indus Chai, Tianyou Northeastern Univ Wang, Hong The Univ. of Manchester 12:00-12:20 WeM4.6 Optimal Energy Management of a Building Cooling System with Thermal Storage: A Convex Formulation, pp Ioli, Daniele Falsone, Alessandro Prandini, Maria WeA1 Scheduling, Optimization, and Control (Regular Session) Chair: Li, Zukui Pol. Di Milano Pol. Di Milano Pol. Di Milano Co-Chair: Su, Hongye Zhejiang Univ. 13:30-13:50 WeA1.1 Chance Constrained Planning and Scheduling under Uncertainty Using Robust Optimization Approximation, pp Li, Zhuangzhi Li, Zukui 13:50-14:10 WeA1.2 Multi-Product Multi-Stage Production Planning with Lead Time on a Rolling Horizon Basis, pp Lu, Shan Su, Hongye Zhejiang Univ Zhejiang Univ 34

36 Wang, Yue Zhejiang Univ Xie, Lei Zhejiang Univ Zhang, Quanling Zhejiang Univ 14:10-14:30 WeA1.3 Optimization Using ANN Surrogates with Optimal Topology and Sample Size, pp Soumitri M, Srinivas IIT Hyderabad Majumdar, Saptarshi Trddc Mitra, Kishalay IIT Hyderabad 14:30-14:50 WeA1.4 Controller Verification and Parametrization Subject to Quantitative and Qualitative Requirements, pp Andonov, Petar Otto-Von-Guericke Univ. Magdeburg Savchenko, Anton Otto-Von-Guericke Univ. Magdeburg Rumschinski, Philipp Otto-Von-Guericke Univ. Magdeburg Streif, Stefan Ilmenau Univ. of Tech Findeisen, Rolf Otto-Von-Guericke Univ. Magdeburg 14:50-15:10 WeA1.5 Iterative Procedure for Tuning Decentralized PID Controllers, pp Euzébio, Thiago A. M. Univ. Federal De Campina Grande Barros, Péricles R. Univ. Federal De Campina Grande 15:10-15:30 WeA1.6 Stability Margin Interpretation of the SIMC Tuning Rule for PI Controllers and Its Applications, pp Lee, Jietae Sung, Su Whan Edgar, Thomas F. WeA2 Kyungpook National Univ Kyungpook National Univ Univ. of Texas at Austin Spearhead Modeling, Control and Optimization of Energy Generating Systems (Invited Session) Chair: Budman, Hector M. Univ. of Waterloo Co-Chair: de Prada, Cesar Univ. of Valladolid 13:30-13:50 WeA2.1 Optimal Operation of an Energy Integrated Batch Reactor - Feed Effluent Heat Exchanger System (I), pp Jogwar, Sujit Inst. of Chemical Tech Daoutidis, Prodromos Univ. of Minnesota 13:50-14:10 WeA2.2 Radio Frequency Heating for Oil Recovery and Soil Remediation (I), pp Bientinesi, Matteo Consorzio Pol. Tecnologico Magona Scali, Claudio Univ. of Pisa Petarca, Luigi Consorzio Pol. Tecnologico Magona 14:10-14:30 WeA2.3 Optimization of the Cyclic Operation of a Continuous Biobutanol Fermentation Process Integrated with Ex-Situ Adsorption Recovery (I), pp Kim, Boeun Eom, Moon-Ho Jang, Hong Lee, Jay H. Kaist GS Caltex Kaist Kaist 14:30-14:50 WeA2.4 Plant-Wide Hierarchical Optimal Control of a Crystallization Process (I), pp Mazaeda, Rogelio Univ. of Valladolid Podar Cristea, Smaranda Univ. of Valladolid de Prada, Cesar Univ. of Valladolid 14:50-15:10 WeA2.5 Optimal Low Temperature Charging of Lithium-Ion Batteries (I), pp Suthar, Bharatkumar Washington Univ. in Saint Louis Braatz, Richard D. Massachusetts Inst. of Tech Subramanian, Venkat Univ. of Washington, Seattle Sonawane, Dayaram Nimba Univ. of Washington, Seattle 15:10-15:30 WeA2.6 Robust Optimization of Competing Biomass Supply Chains under Feedstock Uncertainty (I), pp Zamar, David Sebastian Gopaluni, Bhushan Sokhansanj, Shahab Newlands, Nathaniel WeA3 Univ. of British Columbia Univ. of British Columbia Univ. of British Columbia Science and Tech. Branch, Agriculture and Agri-Food Canada Wedgemount Modeling and Optimization of Biological Systems (Regular Session) Chair: Yue, Hong Univ. of Strathclyde Co-Chair: Chachuat, Benoit Imperial Coll. London 13:30-13:50 WeA3.1 A Two-Level Approach for Fusing Early Signaling Events and Long Term Cellular Responses, pp Rudolph, Nadine Otto-Von-Guericke-Univ. Magdeburg Meyer, Tina Otto-Von-Guericke-Univ. Magdeburg Franzen, Kristina Otto-Von-Guericke-Univ. Magdeburg Garbers, Christoph Univ. of Kiel Schaper, Fred Otto-Von-Guericke-Univ. Magdeburg Streif, Stefan Ilmenau Univ. of Tech Dittrich, Anna Otto-Von-Guericke-Univ. Magdeburg Findeisen, Rolf Otto-Von-Guericke-Univ. Magdeburg 13:50-14:10 WeA3.2 Plant-Wide Optimization of a Full-Scale Activated Sludge Plant with Anaerobic Sludge Treatment, pp Puchongkawarin, Imperial Coll. London Channarong Fitzgerald, Shona Sydney Water Chachuat, Benoit Imperial Coll. London 14:10-14:30 WeA3.3 Agent-Based Modeling of Vascularization in Gradient Tissue Engineering Constructs, pp Bayrak, Elif Seyma Akar, Banu Xiao, Nan Mehdizadeh, Hamidreza Somo, Sami Brey, Eric Illinois Inst. of Tech Illinois Inst. of Tech Illinois Inst. of Tech Illinois Inst. of Tech Illinois Inst. of Tech Illinois Inst. of Tech 35

37 Cinar, Ali Illinois Inst. of Tech 14:30-14:50 WeA3.4 Nonlinear Model Predictive Control of a Wastewater Treatment Process Fitted with a Submerged Membrane Bioreactor, pp Araujo Pimentel, Guilherme Univ. De Mons Rapaport, Alain Inra Vande Wouwer, Alain Univ. De Mons 14:50-15:10 WeA3.5 Computational Modeling of Fed-Batch Cell Culture Bioreactor: Hybrid Agent-Based Approach, pp Bayrak, Elif Seyma Illinois Inst. of Tech Wang, Tony Amgen Inc Cinar, Ali Illinois Inst. of Tech Undey, Cenk Amgen Inc 15:10-15:30 WeA3.6 Optimal Experimental Design for an Enzymatic Biodiesel Production System, pp Yu, Hui Yue, Hong Halling, Peter WeA4 Fault Detection and Identification (Regular Session) Chair: Van Impe, Jan F.M. Univ. of Strathclyde Univ. of Strathclyde Univ. of Strathclyde Black Tusk KU Leuven Co-Chair: Qin, S. Joe Univ. of Southern California 13:30-13:50 WeA4.1 Robust Leakage Detection and Interval Estimation of Location in Water Distribution Network, pp Kim, Yeonsoo Lee, Shin Je Park, Taekyoon Lee, Gibaek Suh, Jung Chul Lee, Jong Min Seoul National Univ Seoul National Univ Seoul National Univ Korea National Univ. of Transportation Samchully Seoul National Univ Li, Gang Univ. of Southern California Yuan, Tao Univ. of Southern California Qin, S. Joe Univ. of Southern California Chai, Tianyou Northeastern Univ 15:10-15:30 WeA4.6 Process Monitoring Based on Recursive Probabilistic PCA for Multi-Mode Process, pp Zhang, Zhengdao Peng, Bican Xie, Linbo Peng, Li WeKA1 Keynote 11 (Keynote Session) Chair: Grover, Martha Jiangnan Univ Jiangnan Univ Jiangnan Univ Jiangnan Univ Georgia Inst. of Tech. Co-Chair: Bonvin, Dominique EPFL 15:50-16:20 WeKA1.1 Artificial Pancreas: From In-Silico to In-Vivo, pp Messori, Mirko Cobelli, Claudio Magni, Lalo WeKA2 Keynote 12 (Keynote Session) Chair: Guay, Martin Co-Chair: Pannocchia, Gabriele Univ. of Pavia Univ. of Padova Univ. of Pavia Spearhead Queen's Univ. Univ. of Pisa 15:50-16:20 WeKA2.1 Design of a Smart Adaptive Control System, pp Kinoshita, Takuya Yamamoto, Toru Hiroshima Univ Hiroshima Univ 13:50-14:10 WeA4.2 Stochastic Fault Diagnosis Using a Generalized Polynomial Chaos Model and Maximum Likelihood, pp Du, Yuncheng Univ. of Waterloo Duever, Thomas Ryerson Univ Budman, Hector M. Univ. of Waterloo 14:10-14:30 WeA4.3 Fault Diagnosis Using Concurrent Projection to Latent Structures, pp Pan, Johnny Univ. of Southern California Dong, Yining Univ. of Southern California Qin, S. Joe Univ. of Southern California 14:30-14:50 WeA4.4 Fault Identification in Batch Processes Using Process Data or Contribution Plots: A Comparative Study, pp Wuyts, Sam KU Leuven Gins, Geert KU Leuven Van den Kerkhof, Pieter KU Leuven Van Impe, Jan F.M. KU Leuven 14:50-15:10 WeA4.5 Dynamic Time Warping Based Causality Analysis for Root- Cause Diagnosis of Nonstationary Fault Processes, pp

38 Author Index A Abedini, Hossein...MoP Acioli Junior, George...MoP Adamson, Richard...MoP Afzal, Muhammad Shahzad...TuM Ahmad, Hassan...TuP Ahmed, Salim...TuM TuP Akar, Banu...WeA Al Kalbani, Fahad...MoP Al-Naumani, Yahya Hamood...MoP Allgower, Frank...MoM1 C...MoM MoKA1 CC Alvarez, Jesus...WeM WeM4 CC...WeM Amribt, Zakaria...WeM Amrit, Rishi...MoPLP.1 1 Anderson, Timothy L....MoM Andonov, Petar...WeA Araujo Pimentel, Guilherme...WeM WeA Arifin, B. M. Sirajeel...MoM Armaou, Antonios...TuA Arrieta, Orlando...MoP Azari Dorcheh, Kamran...WeM B Babaei Pourkargar, Davood...TuA Bacci di Capaci, Riccardo...TuM Backstrom, Johan...MoM MoRT1.1 *...WeM Badillo-Corona, Agustín...TuP Bahakim, Sami Saeed...TuP Bajcinca, Naim...MoA3 CC...MoA Bandi, Apeksha...MoP Bao, Jie...MoP Bao, Jie...TuA1 CC...TuA TuA Baratti, Roberto...WeM WeM Barazandegan, Melissa...MoP Barros, Péricles R....MoA MoP WeA Barroso, Henrique C....MoP Barton, Paul...MoA Bartusiak, Donald...MoPLP C...MoA2 CC...MoRT1.1 * Bathelt, Andreas...MoP Bäthge, Tobias...MoM Bavdekar, Vinay...MoP Bayer, Florian...MoM Bayrak, Elif Seyma...WeA WeA Benavides, Micaela...WeM Bennett, Ryan...MoM Bharmal, Hussain...MoP Bhartiya, Sharad...MoP Bhaumik, Suvomoy...TuM Biegler, Lorenz T....MoA WeM1 C...WeM Bientinesi, Matteo...WeA Billeter, Julien...MoA Bogaerts, Philippe...WeM Bonvin, Dominique...MoA MoA MoRT1.1 *...TuKM WeKA1 CC Botelho, Viviane Rodrigues...TuA Braatz, Richard D....WeA Brandt, Gustavo...TuM Brasio, Ana S R...MoP Brey, Eric...WeA Bruwer, Mark-John...TuKM Budman, Hector M....MoA2 C...TuP WeA2 C...WeA Bullinger, Eric...TuP C Cai, Yijun...MoA Cang, Wentao...TuP Canney, William...MoPLP.1 1 Cao, Yi...TuM Cao, Yuping...TuM Cao, Zhixing...MoKA Cardin, Marlene...TuKM Carrasco, Juan C....TuA Carrette, Pierre...MoPLP.1 1 Castillo, Ivan...MoP Cech, Martin...TuP TuP Chachuat, Benoit...MoM WePLP WeA3 CC...WeA Chai, Tianyou...TuP WeM WeA Chairez, Isaac...TuP Chen, Chun-Yu...TuM Chen, Fengwei...TuP Chen, Hong...MoP TuKM2 CC Chen, Kuilin...MoP Chen, Lei...TuP Chen, Tongwen...MoP TuM4 CC...TuM TuM TuM WeM Chen, Ye...MoA Chen, Zhigang...MoP Cheng, Jinxu...MoA Cheng, Wen...TuM TuA Chiang, Leo...MoP Chmelyk, Terrance...MoRT1.1 *...TuA Choi, Gobong...MoP Choudhury, M.A.A. Shoukat...TuM Christofides, Panagiotis D....MoM MoA TuP Cinar, Ali...WeA WeA Clermont, Gilles...WeKM Cobelli, Claudio...WeKA Cong, Ya...TuA Cott, Barry...MoPLP MoRT1.1 * Couenne, Francoise...WeM2 CC...WeM Coutinho, Daniel...WeM Crose, Marquis...MoA D Dai, Lizhen...MoA

39 Daoutidis, Prodromos...TuM2 CC...TuM WeA Dasani, Sridhar...MoP De La Fuente, Maria Jesus...TuM de Oliveira, Vinicius...TuA de Prada, Cesar...MoA TuM3 C...TuM WeA2 CC...WeA Deng, Xiaogang...TuM Deschênes, Jean-Sébastien...WeM Dewasme, Laurent...MoM WeM WeM Ding, Feng...MoP TuP TuP Ding, Qiang...TuM TuA Ding, Yongsheng...TuP Dittmar, Rainer...MoP Dittrich, Anna...WeA Dochain, Denis...MoKM2 CC...TuP WeM2 C...WeM WeM WeM WeM Domlan, Elom Ayih...MoA Dong, Shijian...TuP Dong, Yining...MoM WeA Doraj, Vimal...TuM Dougherty, Sean...TuA Du, Wenli...MoP TuM Du, Yuncheng...WeA Dubljevic, Stevan...MoM4 C...MoM Duchesne, Carl...WeM Duever, Thomas...WeA Dufour, Pascal...TuM Dughman, Shukri...TuP Dumont, Guy...MoM Dumur, Didier...WeM Duraiski, Ricardo...TuA E Edgar, Thomas F....WeA Eisenschmidt, Holger...MoA El-Farra, Nael H....MoP2 CC...MoP TuM2 C...TuM TuP Ellis, Matthew...MoM Engell, Sebastian...MoM MoA TuM WeM Eom, Moon-Ho...WeA Esmaili, Ali...MoA Espejo, Aris...MoM MoA MoRT1.1 * Espinoza, Bolaños, Mauricio...MoP Euzébio, Thiago A. M....WeA F Falsone, Alessandro...WeM Farenzena, Marcelo...TuA Faulwasser, Timm...MoA1 C...MoA TuKM Feng, Enbo...MoA Fernandes, Natercia C.P....MoP Fernandes, Sofia...WeM Findeisen, Rolf...MoM TuP TuKA2 C...WePLP C...WeKM1 CC...WeM WeA WeA Fitzgerald, Shona...WeA Forbes, J. Fraser...MoP Forbes, Michael Gregory...MoM TuM WeM Fosbøl, Philip Loldrup...TuM Foss, Bjarne...MoA TuM WeM Franzen, Kristina...WeA Fu, Jun...TuP Fujiwara, Koichi...MoM Funnell, Jay...MoP G Gani, Rafiqul...WeM Gao, Furong...MoM MoA4 C...MoA MoKA TuP Gao, Weihua...MoA Gao, Xinqing...MoA Garbers, Christoph...WeA Garcia-Sandoval, Juan Paulo...TuP WeM WeM Gaspar, Erik...TuP Gaspar, Jozsef...TuM Gates, Ian...MoM TuM1 CC...TuM Ge, Zhiqiang...TuA Geng, Zhiqiang...TuP Ghosh, Kaushik...TuA Gins, Geert...WeA Givry, Sebastien...WeM Gomez Sayalero, Elena...TuM Gonzalez, Karen Vanessa...WeM Gonzalez-Alvarez, Victor...TuP Gopaluni, Bhushan...MoM TuM TuA3 C...TuA TuP WePLP CC...WeA Grelet, Vincent...TuM Griffith, Devin...WeM Grote, Wolfgang...TuA Grover, Martha...MoA WeKA1 C Guay, Martin...MoM MoRT1 C...TuPLP C...TuA1 C...TuA TuA WeM WeKA2 C Gudi, Ravindra...MoP TuP2 C...TuP WeKM2 C Guo, Fan...TuP

40 Gupta, Anish...TuP Gutierrez, Gloria...TuM H Halling, Peter...WeA Hamadah, Hamza...TuM Hamroun, Boussad...WeM Hanssen, Kristian Gaustad...MoA Hao, Kuangrong...TuP Hariprasad, K...MoP Hasan, Agus...MoM Hashemi, Reza...TuM Hazama, Koji...MoM He, Ning...WeM Heirung, Tor Aksel N....TuM WeM Heo, Jae Pil...TuM Heo, Seongmin...TuM Ho, Megan...MoP Hoang, Ngoc Ha...WeM WeM Hobbs, Martin...MoP Hofmann, Steffen...MoA Houska, Boris...MoM WePLP Hu, Wenkai...TuM TuM Hu, Yunfeng...MoP Huang, Biao...MoPLP CC...MoM MoM MoM MoA MoP Huang, Dexian...MoA TuM Huang, Linzhe...TuM Huang, Min...TuP Hudon, Nicolas...MoM WeM WeM WeM Huusom, Jakob Kjøbsted...WeM I Ikejiri, Masataka...WeM Imtiaz, Syed...TuM Ioli, Daniele...WeM J Jacobsen, Elling W...MoA Jahanshahi, Esmaeil...MoP Jamaludin, Mohammad Zamry...TuP Jampana, Phanindra...TuA Janardhanan, Vinod M....TuA Jang, Hong...WeA Jäschke, Johannes...TuA Jelali, Mohieddine...MoP Jia, Yao...WeM Jiang, Aipeng...TuM TuA Jiangzhou, Shu...TuM Jin, Ying...TuP Jogwar, Sujit...WeA Johansen, Tor Arne...MoM Jones, Colin N....MoKM Jørgensen, John B....MoKA TuM TuP2 CC Jost, Michael...TuA Jung, Tae Yeong...MoA K Kaasa, Glenn-Ole...MoM Kadali, Ramesh...MoA TuA Kalamatianos, Dimitrios...TuP Kano, Manabu...MoM MoA MoKA2 C...TuKA1 C Karimi, Hadiseh...MoM Kawajiri, Yoshiaki...MoA Khan, Faisal I...TuM Khatir, Ali Ahmadi...MoKM Kim, Boeun...WeA Kim, Dong Hyun...TuM Kim, Jong Woo...MoP Kim, Sin...TuM Kim, Yeonsoo...WeA King, Jared...MoA King, Rudibert...MoA WeM3 C...WeM Kinoshita, Takuya...WeKA Knab, Timothy...WeKM Koegel, Markus J....WeM Koswara, Andy...MoA Krewer, Ulrike...MoKM1 C...TuA Kubal, Nandkishor...TuA Kulkarni, Kedar...MoP Kumar, Divya...MoA TuP Kumar, Kunal...TuM Kwon, Joseph...MoA4 CC...MoA TuP L Lai, Shiqi...TuM Lau, Eric...TuM Lauzon-Gauthier, Julien...WeM Le Gorrec, Yann...WeM Lee, Gibaek...WeA Lee, Hyun Chan...TuM Lee, Jay H....MoKM1 CC...MoA1 CC...MoA MoRT1.1 *...WeA Lee, Jietae...TuM WeA Lee, Jong Min...MoP WeA Lee, Shin Je...WeA Leithead, William...MoP Lemort, Vincent...TuM Li, Chen...TuM Li, Dan...MoP Li, Gang...WeA Li, Haoran...TuP Li, Huayu...MoA Li, Lijuan...TuA Li, Long...MoA Li, Shaoyuan...TuP Li, Xiang...MoP Li, Zhengming...TuP Li, Zhuangzhi...WeA Li, Zukui...MoKM2 C...MoM2 C...MoM MoM WeA1 C...WeA Liang, Yuan...MoP Lima, Fernando V....TuA Lima, Rafael...MoA Linn, Richard...MoPLP.1 1 Liu, Andong...TuM Liu, Bing...TuP

41 Liu, Fei...MoP Liu, Jinfeng...MoM MoM TuA Liu, Ranran...TuP Liu, Su...MoM Liu, Tao...TuP Liu, Tianbo...MoP Liu, Yanjun...TuP Liu, Zheng...TuKM Loewen, Philip D....MoM Lopes, Filipa...WeM Lu, Jingyi...MoKA Lu, Liang...TuP Lu, Shan...WeA Lu, Zhou...TuP Luan, Xiaoli...MoP Lucia, Sergio...MoM1 CC...MoM WeM1 CC...WeM Luo, Linkai...MoM Lymperopoulos, Ioannis...MoKM Lyu, Wenxiang...MoA M Ma, Ruicheng...TuP MacGowan, John...MoM TuM Macgregor, John F....TuKM Magni, Lalo...WeKA Mahajani, Sanjay...MoP Maiworm, Michael...MoM Majumdar, Saptarshi...WeA Mansouri, Seyed Soheil...WeM Marshman, Devin James...TuA Martinez, Alex...MoPLP.1 1 Mazaeda, Rogelio...WeA McAuley, K.B....MoM MoA3 C...WeKM2 CC McClure, Ken...TuP McLellan, P. James...TuA Mehdizadeh, Hamidreza...WeA Mehta, Siddharth...TuP Mendez, Patricio...MoP Mesbah, Ali...MoM3 C...MoM TuKA2 CC Messori, Mirko...WeKA Metzger, Mieczyslaw...WeM Meyer, Tina...WeA Mhaskar, Prashant...TuKA1 CC Miao, Yu...MoM MoA Mier, Dominik...TuA Miletic, Ivan...TuKM Mitra, Kishalay...MoP WeA Mittal, Prateek...MoP Miyano, Takuya...MoA Mizumoto, Ikuro...WeM Möllenbruck, Florian...TuA Monder, Dayadeep Singh...TuA2 CC...TuA Monnigmann, Martin...MoKA1 C...TuKM2 C...TuA2 C...TuA Montague, Gary...MoP Moreno, Jaime A....MoKM MoM Mukhtyar, Vishwa A....MoP Muller, Matthias A....MoM N Na, Youngseung...TuA Nadri, Madiha...TuM Nagy, Zoltan K....MoA Najera, Isrrael...WeM Nallasivam, Ulaganathan...TuA Napasindayao, Trina...TuP Navia, Daniel...MoA Nayhouse, Michael...MoA TuP Neddermeyer, Flavia...WeM Newlands, Nathaniel...WeA Nghiem, Truong...MoKM Ni, Dong...MoA TuP Nie, Yisu...MoA Nikoofard, Amirhossein...MoM2 CC...MoM P Padhiyar, Nitin...MoP TuP Palazoglu, Ahmet N....MoP TuM Pan, Haitian...MoA Pan, Johnny...WeA Pan, Tianhong...TuP Pannocchia, Gabriele...TuM3 CC...TuM WeKA2 CC Pareau, Dominique...WeM Park, Kiho...MoP Park, Taekyoon...WeA Parker, Robert S....WeKM Patel, Narendra...MoP TuP Patwardhan, Rohit...TuM Patwardhan, Sachin C....MoP TuM1 C...TuM Paulen, Radoslav...WePLP Peng, Bican...WeA Peng, Di...TuP Peng, Li...WeA Perepu, Satheesh Kumar...TuP Perić, Nikola...WePLP Perrier, Michel...MoKA2 CC Pessoa, Carolina de Marco...TuP Petarca, Luigi...WeA Petersen, Lars Norbert...MoKA Petit, Nicolas...TuKA Phong Mai, T....WeM Podar Cristea, Smaranda...WeA Polisetty, Venkata Goutham...TuA Pollard, Robert W....MoP Popli, Khushaal...MoM Porru, Marcella...WeM Prakash, Jagadeesan...MoP Prandini, Maria...WeM4 C...WeM Prasad, Vinay...MoM MoM3 CC...MoM MoP WeKM1 C Puchongkawarin, Channarong...WeA Purkayastha, Sagar Neel...TuM Purohit, Jalesh...MoP Q Qi, Fei...TuA Qian, Feng...MoP TuM Qin, S. Joe...MoM TuPLP.1 520

42 ...TuA3 CC...TuA TuA WeA4 CC...WeA WeA Qin, Yan...MoA Qureshi, Faran Ahmed...MoKM R Rahim, Shahed...MoM Rajyaguru, Jai...MoM WePLP Ranjan, Rajesh...MoP Ranzan, Cassiano...MoP TuP Ranzan, Lucas...MoP Rao, Christopher V...WeKM Rapaport, Alain...WeA Rashedi, Mohammad...MoM Rasoulian, Shabnam...WeM Rawlings, James B...MoKA Readman, Mark C....TuP Reiche, Thomas...TuM Reitinger, Jan...TuP Ren, Lihong...TuP Ren, Mifeng...TuP Ricardez-Sandoval, Luis Alberto...TuP WeM Richelle, Anne...WeM Ricker, N. Lawrence...MoP Rippon, Lee...MoM Rocha-Cózatl, Edmundo...MoM Rodrigues, Diogo...MoA Rodríguez-Blanco, Tania...MoA Roginski, Robert T....MoA Rojas, Jose David...MoP Romanenko, Andrey...MoP Rossiter, J. Anthony...MoP TuP Rossner, Niko...MoA WeM Rousseau, Ronald W....MoA Rudolph, Nadine...WeA Rumschinski, Philipp...WeA S Sales Cruz, Mauricio...WeM Samavedham, Lakshminarayanan...TuP Sammaknejad, Nima...MoA Samuel, Raphael T....TuM Sanders, R. Sean...MoA Sarabia, Daniel...MoA TuM Savchenko, Anton...WeA Sbarciog, Mihaela...MoM Scali, Claudio...MoP2 C...TuKM1 C...TuM WeA Schaper, Fred...WeA Schilling, Ricardo...TuM Schlegel, Milos...TuP TuP Schliemann-Bullinger, Monica...TuP Schofield, Brad...MoP Senthamaraikkannan, Gouthami...MoM Sepúlveda-Gálvez, Alfonso...TuP Shah, Sirish L....MoM MoP MoRT1 CC...TuPLP CC...TuKM1 CC...TuM4 C...TuM Shahrokhi, Mohammad...MoP Shang, Chao...MoA Shao, Zhijiang...MoP Sharma, Girish...MoP Shen, Qianyan...MoP Shi, Dawei...WeM Shi, Hongbo...TuP Shukeir, Eliyya...TuA Siam Sundar, Kapil Arasu...MoP Silcock, Andy...MoP Singh, Abhay...MoPLP.1 1 Singh, Gurpreet...TuP Singhal, Martand...MoA Sivalingam, Selvanathan...MoP Skarda, Radek...TuP Skogestad, Sigurd...TuA Skrovanek, Thomas...MoPLP.1 1 Skupin, Piotr...WeM Sokhansanj, Shahab...WeA Somo, Sami...WeA Sonawane, Dayaram Nimba...WeA Song, Zhi-Huan...TuA Soumitri M, Srinivas...WeA Streif, Stefan...MoM WeA WeA Su, Hongye...MoP WeA1 CC...WeA Subramanian, Sankaranarayanan...MoM Subramanian, Venkat...WeA Suh, Jung Chul...MoP WeA Sundmacher, Kai...MoA Sung, Su Whan...WeA Suthar, Bharatkumar...WeA Swartz, Christopher L.E....TuP T Takagi, Taro...WeM Talati, Anurag...MoP Tan, Feiqi...MoP Tanabe, Shuichi...MoA Tangirala, Arun K....TuP Tebbani, Sihem...WeM Tessier, Jayson...WeM Thorigné, Aurore...WeM Tian, Xuemin...MoM TuM Tippett, Michael James...TuA TuA Tong, Chudong...MoP Trierweiler, Jorge Otávio...MoP TuA TuP Trierweiler, Luciane Ferreira...MoP TuP Trifkovic, Milana...TuM Trollberg, Olle...MoA Tsai, Yiting...TuA U Uchimaru, Taku...MoM Undey, Cenk...WeA V Vafa, Ehsan...MoP Valiquette, Jean...MoPLP.1 1 Valluru, Jayaram...MoP Van den Kerkhof, Pieter...WeA Van Impe, Jan F.M....WeA4 C...WeA Vande Wouwer, Alain...MoM4 CC...MoM WeM3 CC...WeM WeM WeM

43 ...WeA Vandermeulen, Isaac...TuA Vargas, Alejandro...MoKM Vignesh, S V...MoP Vilanova, Ramon...MoP Villanueva, Mario E....MoM WePLP Vu, Ky...TuM W Wang, Fuli...TuA Wang, Hangzhou...TuM Wang, Hong...TuP WeM Wang, Jiadong...WeM Wang, Jian...TuM Wang, Jiandong...TuM Wang, Mengling...MoP Wang, Mengling...TuP Wang, Ping...MoM Wang, Ruigang...TuA Wang, Tingren...MoP Wang, Tony...WeA Wang, Xiaonan...TuM Wang, Xuehai...TuP Wang, Yanjiao...TuP Wang, Yanqing...TuP Wang, Youqing...MoA Wang, Yue...WeA Wang, Zhiqiang...MoP Wei, Min...MoP Wei, Shaolong...MoA Wenzel, Simon...MoA Wise, Barry M....MoA Woodley, John M....WeM Wu, Ouyang...MoP Wuyts, Sam...WeA X Xiao, Nan...WeA Xie, Lei...MoA MoP WeA Xie, Li...TuP Xie, Linbo...WeA Xing, Chang Xin...TuA Xing, Changxin...TuM Xu, Fangwei...MoM MoA Xu, Ling...TuP Xu, Xiaodong...MoM Xu, Yuan...TuP Y Yamamoto, Toru...WeKA Yang, Chaohe...MoM Yang, Dae Ryook...MoP Yang, Fan...MoA TuM Yang, Gang...MoA Yang, Hui...MoA Yang, Huizhong...TuP Yang, Minglei...MoP Yang, Wen...TuP Yang, Yu...MoA Yao, Ke...TuP Yao, Yuan...TuM Ydstie, B. Erik...WeM Yoshizaki, Ryosuke...MoA Yousefi, Mahdi...MoM Yu, Hui...WeA Yu, Jie...MoP Yu, Li...TuM Yuan, Tao...WeA Yuan, Zhihong...MoM Yue, Hong...MoP WeA3 C...WeA Z Zamar, David Sebastian...WeA Zang, Hao...TuM Zavala, Victor M....TuKA Zenith, Federico...MoP TuA Zhang, Jianhua...TuP Zhang, Jie...MoP Zhang, Jing...MoM Zhang, Quanling...WeA Zhang, Rongchao...TuM Zhang, Wen-An...TuM Zhang, Zhengdao...WeA Zhao, Chunhui...MoA Zhao, Jinghua...MoP Zheng, Chaoxu...TuA Zheng, Yi...MoM TuP Zheng, Ying...TuA Zhou, Dahan...TuA Zhou, Jack...MoPLP.1 1 Zhou, Mengfei...MoA Zhou, Weijun...WeM Zhu, Qiang...MoP Zhu, Qunxiong...TuP

44 B Batch Process Modeling and Control E Energy Processes and Control M Model-based Control Keyword Index MoA3.2, MoA3.6, MoA4.1, MoA4.2, MoA4.3, MoA4.4, MoA4.5, MoA4.6, MoKA2.1, MoM3.3, MoP2.3, MoP2.5, MoP2.27, TuA2.6, TuKM1.1, TuP2.1, TuP2.8, TuP2.11, TuP2.19, TuP2.23, TuP2.26, TuP2.27, WeA2.1, WeA2.4, WeA2.5, WeA3.5, WeA4.4, WeM2.4, WeM2.5, WeM3.1, WeM3.4, WeM3.6, WeM4.2 MoA2.1, MoA2.2, MoA2.4, MoKM1.1, MoM1.1, MoM2.2, MoM3.1, MoP2.6, MoP2.9, MoP2.14, MoP2.16, MoP2.17, MoP2.24, MoP2.25, MoP2.30, MoP2.32, TuA2.3, TuA2.4, TuA2.5, TuKA1.1, TuM2.1, TuM2.2, TuM2.3, TuM2.4, TuM2.5, TuP2.5, TuP2.17, TuP2.29, WeA2.1, WeA2.2, WeA2.3, WeA2.4, WeA2.5, WeM2.1, WeM2.2, WeM2.3, WeM4.4, WeM4.6 MoA1.1, MoA1.2, MoA1.4, MoA1.5, MoA1.6, MoA3.2, MoA4.3, MoA4.5, MoA4.6, MoKA1.1, MoKA2.1, MoKM1.1, MoM1.1, MoM1.2, MoM1.3, MoM1.4, MoM1.5, MoM1.6, MoM2.2, MoM4.3, MoM4.5, MoM4.6, MoP2.4, MoP2.5, MoP2.11, MoP2.13, MoP2.15, MoP2.26, MoP2.28, MoP2.29, MoP2.31, MoP2.32, MoP2.33, MoPLP.1, TuA1.1, TuA1.2, TuA1.3, TuA1.4, TuA1.5, TuA1.6, TuA2.1, TuA2.2, TuA2.6, TuA3.1, TuA3.2, TuKA2.1, TuKM2.1, TuM1.1, TuM1.2, TuM1.3, TuM1.4, TuM1.5, TuM1.6, TuM2.1, TuM2.3, TuM3.6, TuM4.5, TuP2.5, TuP2.6, TuP2.7, TuP2.8, TuP2.9, TuP2.12, TuP2.13, TuP2.15, TuP2.16, TuP2.17, TuP2.18, TuP2.23, TuP2.24, TuP2.25, TuP2.26, TuP2.29, WeA1.4, WeA1.5, WeA1.6, WeA2.5, WeA3.2, WeA3.4, WeKA1.1, WeKM2.1, WeM1.1, WeM1.2, WeM1.3, WeM1.4, WeM1.5, WeM1.6, WeM2.2, WeM2.4, WeM2.5, WeM2.6, WeM3.2, WeM3.4, WeM4.4, WeM4.5, WeM4.6, WePLP.1 Modeling and Identification MoA1.2, MoA1.6, MoA3.1, MoA3.3, MoA3.4, MoA3.5, MoA3.6, MoA4.4, MoKA1.1, MoM2.3, MoM2.5, MoM2.6, MoM3.1, MoM3.2, MoM3.4, MoM3.5, MoM3.6, MoM4.2, MoM4.3, MoM4.4, MoP2.1, MoP2.2, MoP2.3, MoP2.7, MoP2.8, MoP2.10, MoP2.12, MoP2.13, MoP2.15, MoP2.17, MoP2.19, MoP2.20, MoP2.21, MoP2.23, MoP2.26, MoP2.28, MoP2.29, TuA2.2, TuA2.3, TuA2.5, TuA3.1, TuM1.2, TuM1.3, TuM2.2, TuM2.6, TuM3.1, TuM3.5, TuM4.5, TuP2.1, TuP2.2, TuP2.3, TuP2.4, TuP2.6, TuP2.8, TuP2.10, TuP2.12, TuP2.13, TuP2.14, TuP2.15, TuP2.19, TuP2.20, TuP2.24, O Optimization and Scheduling P Process and Control Monitoring Process Applications TuP2.28, TuP2.30, WeA1.3, WeA1.4, WeA3.1, WeA3.3, WeA3.5, WeA3.6, WeA4.2, WeM1.5, WeM1.6, WeM2.3, WeM3.4, WeM4.1, WePLP.1 MoA1.2, MoA1.3, MoA1.4, MoA1.5, MoA2.2, MoA2.3, MoA2.4, MoA2.5, MoA2.6, MoA3.2, MoA4.1, MoKM1.1, MoKM2.1, MoM1.1, MoM1.2, MoM1.6, MoM2.1, MoM3.1, MoM3.2, MoM3.3, MoM4.2, MoP2.5, MoP2.6, MoP2.8, MoP2.9, MoP2.12, MoP2.13, MoP2.14, MoP2.16, MoP2.22, MoP2.31, MoP2.32, TuA1.1, TuA1.4, TuA1.5, TuA2.6, TuKA2.1, TuKM2.1, TuM1.4, TuM1.5, TuM2.5, TuM2.6, TuM3.4, TuM4.3, TuP2.5, TuP2.6, TuP2.9, TuP2.11, TuP2.20, TuP2.21, TuP2.22, TuP2.25, TuP2.27, TuP2.29, TuP2.31, WeA1.1, WeA1.2, WeA1.3, WeA1.4, WeA2.1, WeA2.3, WeA2.4, WeA2.6, WeA3.1, WeA3.3, WeA3.4, WeA3.6, WeKA1.1, WeM1.1, WeM1.3, WeM1.4, WeM1.5, WeM3.3, WeM4.2, WeM4.6 MoA1.6, MoA2.1, MoA2.3, MoA2.5, MoA3.5, MoA4.2, MoM2.5, MoM4.1, MoM4.3, MoM4.6, MoP2.15, MoP2.17, MoP2.19, MoP2.20, MoP2.21, MoP2.22, MoP2.24, MoP2.25, MoP2.28, MoPLP.1, TuA1.1, TuA1.4, TuA1.5, TuA2.3, TuA3.2, TuA3.3, TuA3.4, TuA3.5, TuA3.6, TuKA1.1, TuKM1.1, TuM1.1, TuM1.2, TuM1.3, TuM3.1, TuM3.2, TuM3.3, TuM3.4, TuM3.5, TuM3.6, TuM4.1, TuM4.2, TuM4.3, TuM4.4, TuM4.5, TuM4.6, TuP2.1, TuP2.7, TuP2.14, TuP2.16, TuP2.21, TuP2.23, TuP2.28, TuP2.31, TuPLP.1, WeA1.2, WeA1.6, WeA4.1, WeA4.2, WeA4.3, WeA4.5, WeA4.6, WeKA2.1, WeKM1.1, WeM1.2, WeM2.6, WeM3.1, WeM3.2, WeM3.3, WeM3.5, WeM4.1, WeM4.3, WeM4.5 MoA1.1, MoA1.5, MoA2.1, MoA2.5, MoA3.4, MoA3.5, MoA3.6, MoA4.1, MoA4.2, MoA4.3, MoA4.6, MoKA1.1, MoKM2.1, MoM1.2, MoM1.3, MoM1.4, MoM1.6, MoM2.1, MoM2.2, MoM2.4, MoM2.5, MoM2.6, MoM3.2, MoM3.3, MoM3.6, MoM4.1, MoM4.2, MoM4.6, MoP2.3, MoP2.4, MoP2.7, MoP2.8, MoP2.10, MoP2.11, MoP2.12, MoP2.18, MoP2.19, MoP2.22, MoP2.24, MoP2.25, MoP2.27, MoP2.29, MoP2.31, MoPLP.1, MoRT1.1, TuA2.2, TuA2.4, TuA3.1, TuKA1.1, TuKM1.1, TuM1.1, TuM1.4, TuM1.5, TuM2.2, TuM2.3, TuM2.4, TuM2.6, TuM3.1, TuM3.5, TuM4.1, TuM4.2, TuM4.3, TuM4.6, TuP2.4, TuP2.15, TuP2.20, TuP2.21, TuP2.24, TuP2.31, WeA1.2, WeA1.3, WeA1.6, WeA2.2, WeA2.3, WeA3.2, WeA3.6, WeA4.1, WeA4.5, WeKM1.1, WeM1.2, WeM1.3, WeM2.4, WeM2.5, WeM3.2, WeM3.3, WeM3.6, WeM4.1, WeM4.2, WeM4.3, WeM4.4, WeM4.5 43

45 Interview with Plenary Speakers Interview with Dr. Barry Cott Q: What is your educational background and current occupation? Barry: I hold Bachelor s, Master s and Ph.D. degrees in chemical engineering, specializing primarily in the topic of process control. I currently work at Shell, and I have been doing so since I graduated from my Ph.D. program over 25 years ago. I am the general manager of the Process Automation, Control and Optimization software team, within an organization known as Technical and Competitive IT (TaCIT). TaCIT sits at the boundary of engineering and IT where people with hybrid skills can be fully leveraged. I supervise approximately 60 people who work on key technologies for our next-generation Advanced Process Control Technology, and I will be discussing our work in that area during the ADCHEM conference. Another area in which I am heavily involved is the cybersecurity aspects around control and safety systems. Q: Could you next briefly touch on your childhood: where you were born, went to school, what your favourite subjects were, and whether you had any role models? Barry: I grew up on the west side of Toronto. My father was a professor at Ryerson University in Toronto for many years. As a child, I remember sitting at the back of his classrooms, drawing with my crayons during his chemistry exams and midterms. Unsurprisingly, I followed his footsteps, to some extent, into the field of chemistry. Therefore, chemical engineering as an interest was a clear and logical choice. A key turning point occurred during my 3 rd year process control class with Dr Gerry Sullivan, who was a new professor at the University of Waterloo at the time. Out of all the professors and experts I met in my generation, he was one who shifted the topic of process control from an abstract, mathematical form to more of a hands-on exercise. Back in 1983, we had primitive computers, but we were still able to run simple simulations on process control systems. After undergrad, I did my Master s in control with Gerry at Waterloo, and a Ph.D. in the UK at Imperial College right after that. I worked with Sandro Macchietto on real-time scheduling and automation technology for batch processes. Q: Could you describe how your graduate education prepared you for your lifetime achievements? Barry: At Waterloo, we were in a cooperative education setup: I went to school for 4 months and worked for 4 months in a repetitive cycle. During my bachelor s, I was working in the continuous-time process control field, doing work for a company (which would now be Nova Chemicals) on control of distillation columns. When I moved to Imperial College, batch processing was popular at that time, and I worked on detailed scheduling of resources in real-time. One highlight would be my work in the cheese and yogurt manufacturing industries, and I have a particularly interesting story to share about that. We had visitors at Imperial College, one of whom was Margaret Thatcher, and I was able to present my work on the control of cheese and yogurt manufacturing processes to her. At the end of the event, people took pictures of me and Margaret Thatcher discussing cottage cheese and yogurt. Q: What recent progressions have you made in your career for the last 25 years? Barry: After I finished my Ph.D., I considered taking a faculty position somewhere. My interests were in the area of Model Predictive Control (MPC). I felt that the application of the concept was still behind: the rate at which these sophisticated concepts were implemented in industry was behind the rate at which they were being developed. I was initially offered a position in southern Ontario to become a process control engineer, because industrial work made sense initially after studying for so many years. I started as a technical specialist, and worked for about 14 years with increasing responsibility, as an expert in Advanced Process Control. In 2003, I moved to the US to oversee the team developing and deploying Shell s advanced process control technologies. The team worked out detailed algorithms on MPC, state estimation, and other concepts. We were also involved with the software development aspects as well, such as implementing control technology into Windows, Distributed Control Systems (DCSs), historians, etc. In 2008, I moved to the Netherlands and managed the regional PACO engineering team for five years before taking up my current role. Q: In your perspective, what major gaps between academics and industry must be bridged over the next few years? 44

46 Barry: I think the biggest problem, for students and industrialists alike, is how to deal with the size and scale of problems that we face today. Most graduate students work with 2x2 systems, but in industry people work with 50x50 systems or larger. This makes the task of solving the dynamic and control laws involved extremely challenging. The field of data analytics and mining require computer scientists and hybrid researchers who look at dynamic data with respect to large-scale problems. Engineers should focus not only on the mathematical details behind algorithms, but also consider the impacts of implementation. In some cases, even if the mathematic background is sound, the algorithm may perform unexpectedly in real-time. We also have to consider the impact of data sizes on the quality of data and predictions, which calls for tighter management and scheduling of resources. As managers, we find that people that work at the boundaries of algorithms, software design, database design, and real-time systems are incredibly competitive in these areas. Q: You mentioned the importance of data analysis and massive volumes of data being generated in the manufacturing industry. Big data has become a buzz word these days, especially in companies such as Google, Facebook, etc. Much research is being conducted using machine learning algorithms. Do you somehow see these ideas and algorithms having an impact on the large volumes of data that we generate in the manufacturing industry, and where do you think the greatest impact is going to be? In my opinion, the recent focus has primarily been on designing controllers and models, and on process analytics, but I rarely encounter people who try to integrate data that is being generated in the different MPC layers in the industry. Do you have any comments on that? Barry: Sure. The paper I wrote demonstrates an example where a MPC was built to put online, and the control engineer knows, at any moment in time, where the setpoints and constraints on the process variables are, as well as any future projections. All these aspects amount to a large volume of data. Trying to deal with one small part of it is already challenging enough. Back in 2007, we took a look at representing these plant states in the form of Markov chains to answer questions like How does an engineer analyze the data to tell whether the plant is hanging around the expected constraint points, and whether the disturbances are returning to the right points? Generally we discovered that interpreting what the dataset was dynamically was not trivial. One novel way to approach this problem is not to mathematically aggregate all of the data, but rather to ask what large sections of data tell about the system. Today, we have metrics to determine whether the quality of the MPC model is affecting predictions. As I mentioned before, I think the approach should be more towards analyzing the data in separate sections, and using tools like Partial Least Squares (PLS) to extract interesting information. Q: Do you have any specific career goals and motivations in life that help you progress through your career? Barry: What continues to drive me is deployment of technology across the business to unlock value. The whole concept of mixing technologies and implementing hybrid solutions as a business has always been attractive to me. The goal is not just to make money for the business, but also to make products with the lowest energy footprint. For example, Shell has plenty of liquefied natural gas plants throughout the world; how can we ensure that we use minimal energy processes to liquefy natural gas? Technology doesn t always develop itself; sometimes you have to create the right environment in order for individuals to apply their strengths to the fullest. Implementing a good idea in a small vicinity of a company (such as Shell) may be an easy task, but trying to introduce change to the whole company can easily require a 5-year program. The process needs to be planned out carefully. Q: Do you have any advice for the young professionals trying to enter the field of control research these days? Barry: I think it s always good to be curious. The need to be a deep specialist in companies like Shell would certainly be true 15 years ago. Today, however, I think people with hybrid skill-sets prove to be extremely competitive. My main caution would be to not overspecialize, because industry does require people who can fundamentally write computer code and algorithms. I would say the academic world pigeon-holes people into specializations. If you other fields interest you, don t be afraid to cultivate them. I am all for research and specialization, but people with hybrid skill-sets that can cross boundaries are probably the most successful people that we have at Shell. Q: So the attitude that you recommend is to not be afraid to specialize, but at the same time keep your other interests active and foster them? Barry: To use myself as an example: I spent time trying to understand how the web and HTML worked. People said to me, Computers? You re a control engineer, why are you spending all that time there for? Several years later, a discussion arose, during which we discussed how human/machine interface groups 45

47 could evolve for advanced control technologies. It required knowledge the possible technologies in web browsers, and at that time few people were able to bring ideas to the discussion. I was one of the few who was able to contribute. Another example is, now in 2015, most of our (Shell s) company operations and technologies are shared on the web. It is all about recognizing how technologies in other areas can mesh with your area of expertise. This is how engineering work in 2015 is different than that of years ago. Q: So you recommend keeping an active approach over the whole area of different opportunities and different fields that are available? Barry: There will always be time to specialize. You never know when something in another field may be applicable to your own. I see people who specialize too deeply, and it becomes increasingly difficult (as one specializes) when the business demands changes in skillsets. We take the opposite approach in Shell; when we bring in new graduates from process control, we re actually having them look at things such as instrumentation and safety systems. This is not because we want them to become experts in those areas, but by recognizing how those systems impact the process, we are making people recognize the interactions between these aspects. Q: So really, it is all about looking at the big picture? Barry: Exactly. I also recommend to people who are starting out to fundamentally realize how your business makes money, and how you can help to move that business value along. One nice thing about advanced process control is that the process constraints are usually very clear, which aspects of product quality should be improved and how all these factors impact the business at large. Sometimes being bogged down on getting the details why things are working and not makes people lose sight of the big picture, which, again, is realizing where the business values are. Q: With that said, do you think that the training that Ph. D. and Masters students are receiving at universities is deemed acceptable, or do you think changes could be made? Barry: I think that it s more of a mindset that I developed over the years, but we ve evolved to a point where the process industry is an applied technology. And that is why I always put a lighter emphasis on the mathematical, theoretical training. Instead, I suggest people to keep looking at how what they re working on can be used to move business forward, not just in the oil/gas industries, but also in other industries that need not be process control. Q: So you ve talked about the industrial ties in the process control field is good, but do you think there are opportunities for more? Barry: I would just suggest that people have the mindset of how to figure out how things can be put together. 25 years ago, there was an obvious opportunity to mix, for example, process control techniques with the yogurt and cottage cheese industry. So again, I think it helps to stay open to understanding what s going on in the industry around us, and what problems they re looking to address. Q: You also talked about the oil/gas industry. How is the current oil price affecting your everyday business? Barry: We have encountered numerous changes today which are challenging many traditional ways of oil/gas production. I would say that the demand for oil still requires traditional pipelines, but at the same time, people need to be coming up with solutions that adapt to the changing infrastructure. Those who succeed consider the constraints and optimize between production efficiency versus economic constraints. Again, this just increases the need for process models and optimization methods, and companies that specialize in these areas (such as Shell) are indeed in a good spot. Q: On the same topic, how do you think the oil price affects the diversification into renewable energy, and are you seeing any kind of shift towards renewable energy due to the drop in oil prices? Is it becoming less or more of a focus? Barry: I have noticed the increasing prevalence of electric cars, as well as fueling stations for these cars, especially in the Netherlands where I live today. The slow displacement of oil/gas and diesel powered cars certainly exists, and obviously the market dictates the direction of changes to some extent. However, I think that people have grown to embrace the concepts of sustainability and renewability, such that even as the prices of oil, gasoline, and diesel drop, people still maintain interest in renewable cars. I think that we are at an inflection point where people see the need in electric vehicles, which raises the demand for electricity. Then the question shifts from how do we produce oil/gas to how do we generate electricity? Shell s stance 46

48 is that energy is always increasing, regardless of what percentage of that total energy is electricity or oil/gas. People will slowly shift away from traditional oil/gas to other renewables, but all these sources of energy will be relevant for another years. Q: As a last question, could you describe your current life, your family, what you like to do in your leisure time, or any sports or hobbies that you may have outside of your academic life? Barry: My wife and I live in the Netherlands, and we have 2 daughters back in Canada. We just became grandparents for the first time a few months ago. It is an exciting experience. We have also taken the advantage of our time here to travel and see as many different places as we can. This is probably the opportunity that has been presented to us by living in Europe for the last few years, and something we spent a lot of time doing for sure. Top left: I am presenting my PhD project to then Prime Minister Margaret Thatcher and her husband Dennis at Imperial College in Professors Sandro Macchietto and Roger Sargent look on. Top right: My daughter, my wife, myself and my son-in-law celebrate the Queens' Birthday in Amsterdam, Netherlands. Bottom left: Cycling in the Netherlands. Bottom right: Hiking in the Canadian Rockies. 47

49 Interview with Dr. Joe Qin Q: What is your educational background and current occupation? Joe Qin: I studied automatic control at Tsinghua University in Beijing for both my Bachelor s and my master s degrees. My Ph.D. degree was in chemical engineering from the University of Maryland, College Park. After my Ph.D., I worked as a principal engineer at Emerson Process Management for 3 years, and developed 2 products. In 1995, I joined the Department of Chemical Engineering at the University of Texas at Austin. I became an Associate Professor in 2000, then became a full professor in After being a professor at University of Texas for 12 years, I switched to the University of Southern California (in Los Angeles) in Currently I am the Vice President at the Chinese University Hong Kong, Shenzhen, which is a new campus in Mainland China. Q: Was there any specific reason that you switched jobs? Joe Qin: As I gained experience in the academic world, I wanted to move on and play a more important role in the area of administration, and influence the direction of research and education. This directly impacts the education that students receive at the school, which in turn impacts the quality of professionals that we are sending out into society. Many colleagues think administration sacrifices your time to do research, but this is something that has to be done by someone. Q: Speaking of playing bigger roles, do you have any plans for that in your future career? Joe Qin: Research definitely remains to be a significant component of my future career, and as I mentioned previously, as the Vice President, my administrative efforts influence the direction of research. I would like to do this throughout China, specifically in building platforms of research-related activities and programs under which young graduates and engineers can thrive. Q: Do you have any advice for young students or engineers who just freshly graduated from university? Joe Qin: In my personal opinion, I think it is important to possess one specific long-term goal, especially for students who are talented. Finding a good job after a sufficient education is easy, but students must be able to recognize the potential of their strengths and talents, and how they can be applied to impact society at large. When students freshly enter a new job, it is easy to simply do as told. The motivation to think about the bigger picture is low. However, as time progresses, one must consider the overall aspects of your business, and make long-term decisions as opposed to decisions based on short-term self-benefits. Think about how these decisions affect society as well. Q: Why did you choose this particular area of research (automatic control) in process control? Joe Qin: Starting from my teenager days 36 years ago, I was one of the first batch of students who had the opportunity to receive higher education, after passing some extremely rigorous entrance exams for university. Despite the heavy competition, I achieved one of the top scores of that time (in the entrance exams) and was accepted into Tsinghua University. At that time, I had a natural aptitude for mathematics, and control seemed like a natural match for my skillset. As I started in the field of automatic control at Tsinghua, I was simultaneously exposed rigorous control theory. In China, automatic control is treated as a discipline by itself, and is considered a highly-respected, Tier-1 discipline for students. I moved to the U.S. for my Ph.D. Studies. Since no stand-alone department existed in the field of process control in the U.S., I chose to study in the field of Chemical Engineering with Tom McAvoy at the University of Maryland. Maryland has an Institute for systems and control, which consolidates research from the various disciplines of Electrical, Mechanical, and Chemical engineering. The exposure to people and ideas from this wide variety of disciplines reinforced my interest in control. Q: To continue on the topic of education preparing graduate students for their future achievements, do you think your graduate education prepared you sufficiently for your career achievements? Joe Qin: Of course! Both my undergraduate education in electrical engineering and my Ph.D. education in chemical engineering trained me to migrate between different disciplines. I was fluent with concepts from electrical engineering and automatic control, as well as basic chemistry and heat transfer concepts. Overcoming the challenges of being exposed to new ideas and qualifying exams in my graduate education prepared me adequately. The field of chemical engineering was new to me; I was probably the first (among my classmates at that time) who chose to do a Ph.D. in a completely unrelated area. This was no easy task which took a significant amount of effort, but paid off in the end in form of transferable, migratory skills. I am 48

50 able to explore new areas and talk to professionals that I otherwise would not have been able to, if not for my diverse education. Q: Could you briefly discuss what you re planning to present at the plenary session during ADCHEM 2015? Joe Qin: I will discuss new trends in the emerging area of process data analytics. Process engineering has, for the past years, traditionally been about collecting a large amount of data. However, computational power has only increased dramatically in the last 10 years, and many of the new opportunities arising from the increase of research in computer science and machine learning have not been realized in the chemical engineering industry. Today everyone is connected to the internet via wireless cellphones and a variety of other electronic gadgets, but how do we process this information? We could apply many of the tools developed in computer science to our chemical processes to extract useful information. This would then aid performance monitoring, control, and optimization, which complements the traditional modelling approaches. That will be the motivation for me to discuss these topics. Q: With the massive amounts of data being collected and generated online today, how do you think the process industry will change? Joe Qin: The use of big data is becoming more obvious now, and certainly will be for the future. In nonchemical engineering areas such as e-commerce and social networking, data is used to guide major decisions. To transfer these theories and methods over to chemical processes and control, we need engineers to apply these methods in the form of a novel solution. We need to think in the direction of how computer science-based data analysis tools can be used in control, optimization and process modelling and monitoring. Q: Could you describe your childhood, perhaps provide any anecdotes or events that you would like to share, that would help the reader relate to you as a plenary speaker? Joe Qin: I was born in a town near Qingdao, which is a coastal area in the Shandong province. Most of my childhood was spent during the Cultural Revolution. For many children of that time, the concept of not having to go to school and work hard was attractive. I did not study much until junior high, because nobody had to. The educational system at school was almost nonexistent; we were barely taught anything of use. By the time I reached high school, the end of the cultural revolution sparked a major political change. Suddenly, young children were encouraged to study because they were given the opportunity to enter college through rigorous exams and competition. I was accepted into Tsinghua University with one of the highest scores, at the age of 16. Most other children older than me were involved in physical labour in the countryside, due to their being caught up in the last years of the cultural revolution. I was too young to be part of that, and was fortunate enough to have both the time to play before junior high school, and the chance to receive good education. At that time, most youngsters in China looked up to great mathematicians as role models. Q: I (Bhushan Gopaluni) also received a good education at the University of Alberta. One of the best professors I ever had was Tongwen Chen. I realize that you and Prof. Chen were close childhood friends and classmates. Do you have anything to say about your friendship? Joe Qin: Tongwen Chen and I studied at Tsinghua University in the same discipline of automatic control. Our dorms were next door, and we worked together closely for 5 years undergrad and 1.5 years during grad school. Tongwen was one of the smartest students ever to exist in the department of control at Tsinghua. We worked together closely and enjoyed our friendship. Moreover, we shared a number of extracurricular activities at Tsinghua meant for the top students. Several years later, both of us left China to pursue our Ph.D. degrees. Interestingly, we were both elected as fellows of IFAC last year at the IFAC World Congress. Out of the 30 years of students graduating from Tsinghua s automatic control department, only the two of us were ever elected as IFAC fellows. Q: You talked about how mathematics played a big role in your choice of education and research. In your opinion, are professors training process engineers correctly? I personally find it hard to attract chemical engineering students with the right aptitude for mathematics to do research in high-level control. Could you comment on how our education system should change (if it should), and if we could improve certain aspects of it to retain students interests in control, and to attract the best students to control engineering? Joe Qin: Given my current role as an administrator and educator, this is of course one of my primary focuses. I think we have to recognize that the times have changed. For example, 30 years ago people found it enjoyable to do mathematical puzzles as a hobby. Now many other activities appear to be more attractive. For mathematics, people have to possess a certain aptitude to find it interesting. In engineering, most 49

51 students find, for example, experimental work more interesting than mathematical theory. Math is an abstract subject and it takes a special process for students to fully understand the concepts. Moreover, we teach significantly less mathematics in engineering today compared to 30 years ago, because most people want a program where even the average student can understand most of the concepts presented and graduate easily. On the other hand, when I was studying 30 years ago, professors cared little about whether students fully digested the content, so they taught all the math they deemed necessary in the appropriate subjects. I would like to add that a wide distribution exists with respect to students mathematical capabilities. In countries like China and Russia, a rigorous mathematical education is retained even today, so we are still able to find people possessing strong abilities in math. Drastic changes in the educational system cannot happen overnight; it has to change over the course of many years. But, for the few people out there who are interested in math, we have to pay more attention for creating an environment that will foster and shape their talents. Q: A trade-off always exists in education, in terms of what should be taught to only the best students and what should be taught to all students. How do you think the balance should shift in engineering today? Joe Qin: Times have changed; professors now have to be aware of their teaching evaluations (by students). When I went to school, no teaching evaluations existed, and even if there were, professors cared little about them. When I was a graduate student, I had a professor who taught us linear algebra, of which less than 10% of the total material was understood by an average student taking the course. However, this course was one of which I learned the most from. Students could not digest the course material easily, because it was taught in such an abstract way. As a student, adapting to different professors teaching styles is a necessary evil. Q: Did you experience any hardships, interesting or life-changing events? We would like to tell your story in such a way that it inspires future students, professors, etc., to help them to achieve goals similar to those that you have achieved in your career. Joe Qin: Most of the life-changing situations I experienced occurred to me when I was still young. When I was a child, the cultural revolution ended when Deng Xiaoping became in charge of China. He restored the opportunities for most children to pursue post-secondary education. That was the reason I got into Tsinghua when I was 16 years old. When I was 11 or 12, I had to figure out how to make a living. Without education as an option, physical labour was the only solution. I explored tailoring as a vocation, as well as carpentry. For example, I was able to construct wooden chairs and other things at the age of 11, a task which few adults (let alone children) can accomplish today. But back then it was necessary, because there was no other method of making a living. I was fortunate enough to not have to waste much time doing physical labour, as the cultural revolution ended. If the revolution did not end in time, I certainly would not be who I am today. The other major life-changing event for me occurred during the 1980s, when I was admitted into the University of Maryland and started working with Tom McAvoy in Chemical Engineering. Q: Could you give us a historical perspective on how you started your research has evolved in so many of these areas? Big data is a major field today; you ve worked in process monitoring, fault detection, system identification, and so on. How did you adapt so quickly to these different disciplines? Joe Qin: The switch to chemical engineering was the most important deciding factor. The interdisciplinary training provided with me the confidence to freely explore the different areas in control, even if those areas were unfamiliar to me at first. At Tsinghua, the rigorous control program prepared me so adequately that by the time I was accepted into Maryland, I was already well-equipped with a strong background in control engineering, and only needed to brush up on process engineering. At the University of Texas, I was presented with many opportunities around semiconductor manufacturing, applying concepts in statistical process control and monitoring. The local industry was also quick to adopt these multivariable statistical techniques, fault detection and diagnosis tools to improve their processes. When I moved to University of Southern California, the opportunity to work with semiconductors was no longer as convenient, as many facilities have been moved to Korea and Taiwan. It was a time to explore the new area of energy. 8 years ago, I started working in the area of energy optimization, looking at upstream oil operations and control. At USC, I was part of a center for smart oil fields, called CiSoft, which was actually a joint venture between USC and Chevron. I have given talks in several different areas, and worked with top scholars worldwide in those areas. For example, I can talk to people in chemometrics, system identification, machine learning, and computer science. Finally, I have published numerous reviews of papers in all these different areas. Last year, I wrote a perspective article which was published as the AIChE Journal s September 2014 issue. I was lucky enough to be invited by the Journal editor, Prof. Ignacio Grossman at Carnegie Mellon to write his paper. This paper just appeared 6 months ago, and was one of the hottest papers ever published by Wiley. 50

52 Q: Tell us a bit about your personal life, family. What do you like to do in your leisure time? Do you play any sports? Joe Qin: Until about 10 years ago, I played tennis, but could not cope up with the strenuous physical efforts required. Now my everyday hobby is playing golf and taking walks. I play golf with friends such as Tom McAvoy at Texas, James Rawlings at Wisconsin, Tom Marlin at McMaster, and Jay Lee in Korea. I have also been part of the Texas Consortium with Tom Edgar and James Rawlings for more than 20 years. Before every consortium meeting we would have a golf game, and that led to good friendships. Q: Thanks for the interview. If you have any interesting photos please share them with us. Joe Qin: Thank you for your time. I think the best attitude is to not boast about myself, my intention is not to boast about my achievements, but to share these events and my thoughts as I get older, with the younger generation of engineers and students. We have a responsibility to help young people by sharing our experiences with them. I look at it this way, and this is why I came forward to do this interview. In the past I would just do my work, and didn t say much to verbally share it with other people. Now my thinking has changed, and I realized it is good to share with young people, both what (I think) is right and what is not right to do. Q: Thank you for everything. Did you want to tell us anything else; was there some question that we missed? Joe Qin: On a final note, I wish to mention the numerous mentors I was fortunate enough to have. Tom McAvoy was my Ph. D. advisor, and a professor who was always enthusiastic about helping young people. Tom was the editor of JPC for 18 years, and is now retired. Another person is Prof. Harmon Ray, who is also very well-known in both process control and the polymer field. He visited Tsinghua in 1988 and gave me the critical, life-changing advice of doing a Ph. D. at Maryland. My colleagues at Texas and Wisconsin, Tom Edgar and James Rawlings were also my mentors and friends in many ways. John MacGregor and Lennart Ljung are two marvelous scholars whose pioneering work in their respective fields, friendship, and the numerous discussions we had in their beautiful houses were both inspiring and memorable. Finally, Tom Marlin, Sirish Shah, Biao Huang are also people I have had many productive conversations with. 51

53 Valley Foyer Level Valley Foyer Entrance To Parkade Women s Men s Service Areas Men s Women s Black Tusk Valley Foyer Load In Entrance Fitzsimmons CHES Breakout (June 8/9) Spearhead A/B Soo Valley CHES storage Wedgemount A/B Exhibitor Stairs to Upper Level (Sea to Sky Ballroom & Grand Foyer) Buffets Coffee Registration Exhibitor Exhibitor Exhibitor Exhibitor Elevator Tantalus Office Office Space Service Areas Theatre Office Space Harmony A/B CHES Breakout (June 8/9) Garibaldi A/B Set for 180 Projection Room Service Areas Storage University of Alberta ADCHEM June 7-10, 2015 Women s Men s Theatre Whistler Way Entrance 52

54 Stage Sea to Sky Ballroom A Service Area Loading Bay Service Area Service Area Sea to Sky Ballroom C Sea to Sky Ballroom B To Valley Foyer Fireplace Elevator Mountain View Room Main Entrance 53