Sistemas com saturação no controle

Size: px
Start display at page:

Download "Sistemas com saturação no controle"

Transcription

1 1 Sistemas com saturação no controle VIII. Estratégias anti-windup - Introdução SOPHIE TARBOURIECH LAAS - CNRS, Toulouse, France Colaboradores principais : J.-M. Gomes da Silva Jr (UFRGS), G. Garcia (LAAS-CNRS), I. Queinnec (LAAS-CNRS)

2 Outline 2 Introduction to anti-windup strategies 1. Introduction 2. A bit of history 3. Problem statement

3 1. Introduction 3 Non Linear Model + Controller The anti-windup techniques represent an alternative to analysis and synthesis methods previously presented Idea: Deal with the saturations but without modifying the controller in the linear region The anti-windup techniques consist in considering the effects of the nonlinearities like saturations a posteriori Idea: introduce some modifications in the original controller in order to mitigate the undesirable effects of the saturation Successfully used in PID controllers Stability analysis [Teel, Morari & co-authors] external stability global stability results application only to open-loop stable systems

4 1. Introduction 4 To summarize, the principe of anti-windup may be represented through the following scheme: w (disturbance) r (reference) u c unconstrained controller y c u 0 u system z (controlled) y (measured) + v 1 v 2 anti windup controller + +

5 1. Introduction 5 The aims: Study of conditions for guaranteing stability (in local and global contexts) of anti-windup schemes To take into account the amplitude limitations on both the input and the output of the system (limited actuator and sensor) In global context: open-loop properties of stability are required when the open-loop system is unstable : local stability. In local context: design the anti-windup gain in order to enlarge the basin of attraction of the closed-loop system Propose numerically efficient procedures to compute the anti-windup gains Different types of anti-windup compensators

6 1. Introduction 6 Experience with application of anti-windup strategies Aeronautical domains: GARTEUR projects, Airbus cooperation Spatial domain: PIROLA project (robust flying launchers type Ariane 5+) Mechanical domain: flexible beam with piezzo-electrical cells (actuator and sensor) Potential spin-off Reduction of validation costs of control laws Better use of actuator (and/or sensors) capacity Possibility to interact with the engineer at the beginning: for example to choose the actuators and/or sensors (allows to reduce their consummation, size, mass...)

7 2. A bit of history 7 From historical point of view, the anti-windup approach may be decomposed in 6 phases. Phase 1. Discovery ( ) Phase 2. Invention ( ) Phase 3. Criticisms (after 1980) Phase 4. Unification (after beginning 1990) Phase 5. Feasibility (after 1990) Phase 6. Implementation procedure and extensions (after from 2000)

8 2. A bit of history 8 Phase 1 - Discovery It is difficult to find any documents related to engineers experiments in the literature. Since 1940, the literature related to the absolute stability intends to better understand the behaviour of linear systems submitted to input saturations. In 1956 [IRE TAC], Lozier identifies the windup problem and explains why the PI controllers are subject to windup phenomena more than the P controllers. The output begins to oscillate after a saturation of the input The integrator goes on being charged during saturation periods

9 2. A bit of history 9 Phase 2 - Invention Modification of the integral action in case of saturation: Lozier (1956): use of a limiter Fertik, Ross (1967): Ad-hoc method for standard PID controllers Phelan (1977), Krikelis (1980): intelligent integrators More general modifications of the controller: Hanus (1980, 1987): conditioning technique Aström (1983): technique based on observer strategies.

10 2. A bit of history 10 Phase 3 - Criticisms In an ACC paper in 1997, Doyle, Smith and Enns present a critic evaluation of conventional anti-windup techniques: no real formal theory potential links with modern multivariable techniques

11 2. A bit of history 11 Phase 4 - Unification Aström and Rundquist (1989, ACC): they unify several techniques via an observer-based approach Kothare, Campo, Morari, Nett (1989 ACC, 1994 Automatica): except for some cases, the previous techniques may be described through linear and static modifications of the controller.

12 2. A bit of history 12 Phase 5 - Feasibility Stability without performance requirements : Horowitz (1983 IJC) Morari, Zafiriou, Irving (1987) Towards stability with performance requirements: Miyamoto, Vinnicombe (1996 CDC) Teel, Kapoor (1987 ECC) Optimal-based controllers: Gilbert, Kolmanovsky, Tan (1995 IJRNC) Shamma (2000 SCL)

13 2. A bit of history 13 Phase 6 - Implementation procedures and extensions Optimization H : Miyamoto, Vinnicombe (1996 CDC) Edwards, Postlethwaite (1998, 1999 Automatica) Linear matrix inequalities: Mulder, Kothare, Morari (1999 ACC), Gomes da Silva Jr., Tarbouriech (2003 CDC) Grimm et al (2001 ACC) Predictive control: Bemporad, Teel, Zaccarian (2002 ACC) Grimm et al (2003 ACC)

14 3. Problem statement 14 For developing our approach, we need to consider A state-space description of the system and controller A description of the amplitude saturation on actuator and sensor blocks Some anti-windup techniques What are available measures for building the anti-windup loops? Tools: A generalized sector condition is used Quadratic Lyapunov function Finsler s Lemma (use of multipliers = extra degrees of freedom) Convex optimization

Sistemas com saturação no controle - VII. VII. Discussões e extensões

Sistemas com saturação no controle - VII. VII. Discussões e extensões 1 Sistemas com saturação no controle VII. Discussões e extensões Sophie Tarbouriech LAAS - CNRS, Toulouse, France Colaboradores principais : J.-M. Gomes da Silva Jr (UFRGS), G. Garcia (LAAS-CNRS), I. Queinnec

More information

ACTIVE Queue Management (AQM) on Transmission

ACTIVE Queue Management (AQM) on Transmission INTERNATIONAL JOURNAL OF INTELLIGENT CONTROL AND SYSTEMS VOL. 17, NO. 2, JUNE 212, 47-52 Towards Linear Control Approach to AQM in TCP/IP Networks Ricardo Augusto BORSOI, and Fernando Augusto BENDER Abstract

More information

PID Controller Design for Nonlinear Systems Using Discrete-Time Local Model Networks

PID Controller Design for Nonlinear Systems Using Discrete-Time Local Model Networks PID Controller Design for Nonlinear Systems Using Discrete-Time Local Model Networks 4. Workshop für Modellbasierte Kalibriermethoden Nikolaus Euler-Rolle, Christoph Hametner, Stefan Jakubek Christian

More information

C21 Model Predictive Control

C21 Model Predictive Control C21 Model Predictive Control Mark Cannon 4 lectures Hilary Term 216-1 Lecture 1 Introduction 1-2 Organisation 4 lectures: week 3 week 4 { Monday 1-11 am LR5 Thursday 1-11 am LR5 { Monday 1-11 am LR5 Thursday

More information

QNET Experiment #06: HVAC Proportional- Integral (PI) Temperature Control Heating, Ventilation, and Air Conditioning Trainer (HVACT)

QNET Experiment #06: HVAC Proportional- Integral (PI) Temperature Control Heating, Ventilation, and Air Conditioning Trainer (HVACT) Quanser NI-ELVIS Trainer (QNET) Series: QNET Experiment #06: HVAC Proportional- Integral (PI) Temperature Control Heating, Ventilation, and Air Conditioning Trainer (HVACT) Student Manual Table of Contents

More information

How to Analyze the Stability of Anti-Windup Control Systems

How to Analyze the Stability of Anti-Windup Control Systems Multiplier Theory for Stability Analysis of Anti-Windup Control Systems* Mayuresh V. Kotharet tchemical Engineering 210-41 California Institute of Technology Pasadena, CA 91125, U.S.A. Manfred ~orari'j

More information

CONTROL SYSTEMS, ROBOTICS AND AUTOMATION Vol. XVI - Fault Accomodation Using Model Predictive Methods - Jovan D. Bošković and Raman K.

CONTROL SYSTEMS, ROBOTICS AND AUTOMATION Vol. XVI - Fault Accomodation Using Model Predictive Methods - Jovan D. Bošković and Raman K. FAULT ACCOMMODATION USING MODEL PREDICTIVE METHODS Scientific Systems Company, Inc., Woburn, Massachusetts, USA. Keywords: Fault accommodation, Model Predictive Control (MPC), Failure Detection, Identification

More information

Control Systems with Actuator Saturation

Control Systems with Actuator Saturation Control Systems with Actuator Saturation Analysis and Design Tingshu Hu Zongli Lin With 67 Figures Birkhauser Boston Basel Berlin Preface xiii 1 Introduction 1 1.1 Linear Systems with Actuator Saturation

More information

Anti-windup compensator for active queue management in TCP networks

Anti-windup compensator for active queue management in TCP networks Control Engineering Practice 11 (23) 1127 1142 Anti-windup compensator for active queue management in TCP networks Kyung-Joon Park a, *, Hyuk Lim a, Tamer Ba-sar b, Chong-Ho Choi a a School of Electrical

More information

Performance of diagonal control structures at different operating. conditions for Polymer Electrolyte Membrane Fuel Cells

Performance of diagonal control structures at different operating. conditions for Polymer Electrolyte Membrane Fuel Cells Performance of diagonal control structures at different operating conditions for Polymer Electrolyte Membrane Fuel Cells Maria Serra (corresponding author), Attila Husar, Diego Feroldi, Jordi Riera Institut

More information

An Industrial Case Study - Control of BeoSound 9000 Sledge System

An Industrial Case Study - Control of BeoSound 9000 Sledge System An Industrial Case Study - Control of BeoSound 9000 Sledge System Zhenyu Yang Department of Computer Science and Engineering, Aalborg University Esbjerg, Niels Bohrs Vej 8, DK-6700 Esbjerg, Denmark. yangcs.aaue.dk

More information

INTERACTIVE LEARNING MODULES FOR PID CONTROL

INTERACTIVE LEARNING MODULES FOR PID CONTROL INTERACTIVE LEARNING MODULES FOR PID CONTROL José Luis Guzmán, Karl J. Åström, Sebastián Dormido, Tore Hägglund, Yves Piguet Dep. de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain.

More information

Keywords: Fuzzy Logic, Control, Refrigeration Systems and Electronic Expansion Valves.

Keywords: Fuzzy Logic, Control, Refrigeration Systems and Electronic Expansion Valves. POTENTIALITIES OF FUZZY LOGIC CONTROL APPLIED TO SMALL VAPOR COMPRESSION REFRIGERATION SYSTEMS Oscar S. H. Mendoza Fábio A. Carvajal José A. Tumialán Gustavo Luiz C. M. de Abreu Universidade Federal de

More information

FAST METHODS FOR SLOW LOOPS: TUNE YOUR TEMPERATURE CONTROLS IN 15 MINUTES

FAST METHODS FOR SLOW LOOPS: TUNE YOUR TEMPERATURE CONTROLS IN 15 MINUTES FAST METHODS FOR SLOW LOOPS: TUNE YOUR TEMPERATURE CONTROLS IN 15 MINUTES Michel Ruel P.E. President, TOP Control Inc 4734 Sonseeahray Drive 49, Bel-Air St, #103 Hubertus, WI 53033 Levis Qc G6W 6K9 USA

More information

Direct Acceleration Feedback Control of Shake Tables with Force. Stabilization

Direct Acceleration Feedback Control of Shake Tables with Force. Stabilization Direct Acceleration Feedback Control of Shake Tables with Force Stabilization Matthew Stehman [1] and Narutoshi Nakata [2] [1] Graduate Student, Department of Civil Engineering, The Johns Hopkins University,

More information

POTENTIAL OF STATE-FEEDBACK CONTROL FOR MACHINE TOOLS DRIVES

POTENTIAL OF STATE-FEEDBACK CONTROL FOR MACHINE TOOLS DRIVES POTENTIAL OF STATE-FEEDBACK CONTROL FOR MACHINE TOOLS DRIVES L. Novotny 1, P. Strakos 1, J. Vesely 1, A. Dietmair 2 1 Research Center of Manufacturing Technology, CTU in Prague, Czech Republic 2 SW, Universität

More information

A Design of a PID Self-Tuning Controller Using LabVIEW

A Design of a PID Self-Tuning Controller Using LabVIEW Journal of Software Engineering and Applications, 2011, 4, 161-171 doi:10.4236/jsea.2011.43018 Published Online March 2011 (http://www.scirp.org/journal/jsea) 161 A Design of a PID Self-Tuning Controller

More information

Controller Design in Frequency Domain

Controller Design in Frequency Domain ECSE 4440 Control System Engineering Fall 2001 Project 3 Controller Design in Frequency Domain TA 1. Abstract 2. Introduction 3. Controller design in Frequency domain 4. Experiment 5. Colclusion 1. Abstract

More information

PID Control. Chapter 10

PID Control. Chapter 10 Chapter PID Control Based on a survey of over eleven thousand controllers in the refining, chemicals and pulp and paper industries, 97% of regulatory controllers utilize PID feedback. Desborough Honeywell,

More information

EECE 460 : Control System Design

EECE 460 : Control System Design EECE 460 : Control System Design PID Controller Design and Tuning Guy A. Dumont UBC EECE January 2012 Guy A. Dumont (UBC EECE) EECE 460 PID Tuning January 2012 1 / 37 Contents 1 Introduction 2 Control

More information

Nonlinear Model Predictive Control: From Theory to Application

Nonlinear Model Predictive Control: From Theory to Application J. Chin. Inst. Chem. Engrs., Vol. 35, No. 3, 299-315, 2004 Nonlinear Model Predictive Control: From Theory to Application Frank Allgöwer [1], Rolf Findeisen, and Zoltan K. Nagy Institute for Systems Theory

More information

Best Practices for Controller Tuning

Best Practices for Controller Tuning Best Practices for Controller Tuning George Buckbee, P.E. ExperTune, Inc. 2009 ExperTune, Inc. Page 1 Best Practices for Controller Tuning George Buckbee, P.E., ExperTune Inc. 2009 ExperTune Inc Summary

More information

How To Design A Missile Control System

How To Design A Missile Control System Overview of Missile Flight Control Systems Paul B. Jackson he flight control system is a key element that allows the missile to meet its system performance requirements. The objective of the flight control

More information

Imag Axis. 80 60 40 20 0 20 40 60 80 Real Axis

Imag Axis. 80 60 40 20 0 20 40 60 80 Real Axis . Electromagnetic Levitation System : An Experimental Approach H. D. Taghirad, M. Abrishamchian, R. Ghabcheloo K. N. Toosi University of Technology Department of Electrical Engineering Tehran, Iran Abstract

More information

Chapter 9: Controller design

Chapter 9: Controller design Chapter 9. Controller Design 9.1. Introduction 9.2. Effect of negative feedback on the network transfer functions 9.2.1. Feedback reduces the transfer function from disturbances to the output 9.2.2. Feedback

More information

Chapter 3 Nonlinear Model Predictive Control

Chapter 3 Nonlinear Model Predictive Control Chapter 3 Nonlinear Model Predictive Control In this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous way. We start by defining a basic NMPC algorithm for constant reference

More information

Real-Time Systems Versus Cyber-Physical Systems: Where is the Difference?

Real-Time Systems Versus Cyber-Physical Systems: Where is the Difference? Real-Time Systems Versus Cyber-Physical Systems: Where is the Difference? Samarjit Chakraborty www.rcs.ei.tum.de TU Munich, Germany Joint work with Dip Goswami*, Reinhard Schneider #, Alejandro Masrur

More information

A Passivity Measure Of Systems In Cascade Based On Passivity Indices

A Passivity Measure Of Systems In Cascade Based On Passivity Indices 49th IEEE Conference on Decision and Control December 5-7, Hilton Atlanta Hotel, Atlanta, GA, USA A Passivity Measure Of Systems In Cascade Based On Passivity Indices Han Yu and Panos J Antsaklis Abstract

More information

Analysis of PID Control Design Methods for a Heated Airow Process

Analysis of PID Control Design Methods for a Heated Airow Process Helsinki University of Technology Faculty of Information and Natural Sciences Department of Mathematics and Systems Analysis Mat-.8 Independent research projects in applied mathematics Analysis of PID

More information

Force/position control of a robotic system for transcranial magnetic stimulation

Force/position control of a robotic system for transcranial magnetic stimulation Force/position control of a robotic system for transcranial magnetic stimulation W.N. Wan Zakaria School of Mechanical and System Engineering Newcastle University Abstract To develop a force control scheme

More information

Brief Paper. of discrete-time linear systems. www.ietdl.org

Brief Paper. of discrete-time linear systems. www.ietdl.org Published in IET Control Theory and Applications Received on 28th August 2012 Accepted on 26th October 2012 Brief Paper ISSN 1751-8644 Temporal and one-step stabilisability and detectability of discrete-time

More information

Modeling and Simulation of a Three Degree of Freedom Longitudinal Aero plane System. Figure 1: Boeing 777 and example of a two engine business jet

Modeling and Simulation of a Three Degree of Freedom Longitudinal Aero plane System. Figure 1: Boeing 777 and example of a two engine business jet Modeling and Simulation of a Three Degree of Freedom Longitudinal Aero plane System Figure 1: Boeing 777 and example of a two engine business jet Nonlinear dynamic equations of motion for the longitudinal

More information

Predictive Control Algorithms for Nonlinear Systems

Predictive Control Algorithms for Nonlinear Systems Predictive Control Algorithms for Nonlinear Systems DOCTORAL THESIS for receiving the doctoral degree from the Gh. Asachi Technical University of Iaşi, România The Defense will take place on 15 September

More information

MLD Model of Boiler-Turbine System Based on PWA Linearization Approach

MLD Model of Boiler-Turbine System Based on PWA Linearization Approach International Journal of Control Science and Engineering 2012, 2(4): 88-92 DOI: 10.5923/j.control.20120204.06 MLD Model of Boiler-Turbine System Based on PWA Linearization Approach M. Sarailoo *, B. Rezaie,

More information

Dr. Yeffry Handoko Putra, S.T., M.T

Dr. Yeffry Handoko Putra, S.T., M.T Tuning Methods of PID Controller Dr. Yeffry Handoko Putra, S.T., M.T yeffry@unikom.ac.id 1 Session Outlines & Objectives Outlines Tuning methods of PID controller: Ziegler-Nichols Open-loop Coon-Cohen

More information

Using Wireless Measurements in Control Applications

Using Wireless Measurements in Control Applications Using Wireless Measurements in Control Applications Terry Blevins, Mark Nixon, Marty Zielinski Emerson Process Management Keywords: PID Control, Industrial Control, Wireless Transmitters ABSTRACT Wireless

More information

State-Space Feedback Control for Elastic Distributed Storage in a Cloud Environment

State-Space Feedback Control for Elastic Distributed Storage in a Cloud Environment State-Space Feedback Control for Elastic Distributed Storage in a Cloud Environment M. Amir Moulavi Ahmad Al-Shishtawy Vladimir Vlassov KTH Royal Institute of Technology, Stockholm, Sweden ICAS 2012, March

More information

Full- day Workshop on Online and offline optimization for humanoid robots. at IEEE IROS 2013 in Tokyo

Full- day Workshop on Online and offline optimization for humanoid robots. at IEEE IROS 2013 in Tokyo Full- day Workshop on Online and offline optimization for humanoid robots at IEEE IROS 2013 in Tokyo Organizers: Eiichi Yoshida, Katja Mombaur, Tom Erez, Yuval Tassa Nov 7, 2013 TALK ABSTRACTS Tamim Asfour

More information

A simple method to determine control valve performance and its impacts on control loop performance

A simple method to determine control valve performance and its impacts on control loop performance A simple method to determine control valve performance and its impacts on control loop performance Keywords Michel Ruel p.eng., Top Control Inc. Process optimization, tuning, stiction, hysteresis, backlash,

More information

Nonlinear Model Predictive Control of Hammerstein and Wiener Models Using Genetic Algorithms

Nonlinear Model Predictive Control of Hammerstein and Wiener Models Using Genetic Algorithms Nonlinear Model Predictive Control of Hammerstein and Wiener Models Using Genetic Algorithms Al-Duwaish H. and Naeem, Wasif Electrical Engineering Department/King Fahd University of Petroleum and Minerals

More information

LOOP TRANSFER RECOVERY FOR SAMPLED-DATA SYSTEMS 1

LOOP TRANSFER RECOVERY FOR SAMPLED-DATA SYSTEMS 1 LOOP TRANSFER RECOVERY FOR SAMPLED-DATA SYSTEMS 1 Henrik Niemann Jakob Stoustrup Mike Lind Rank Bahram Shafai Dept. of Automation, Technical University of Denmark, Building 326, DK-2800 Lyngby, Denmark

More information

Modeling, Analysis, and Control of Dynamic Systems

Modeling, Analysis, and Control of Dynamic Systems Modeling, Analysis, and Control of Dynamic Systems Second Edition William J. Palm III University of Rhode Island John Wiley Sons, Inc. New York Chichester Weinheim Brisbane Singapore Toronto To Louise.

More information

Christophe PRIEUR. oct. 2010- sept. 2011 CNRS Associate Researcher at Gipsa-lab, Grenoble, France

Christophe PRIEUR. oct. 2010- sept. 2011 CNRS Associate Researcher at Gipsa-lab, Grenoble, France Christophe PRIEUR CNRS Senior Researcher (Directeur de Recherche CNRS) Born on May 14, 1974 at Essey-lès-Nancy, France Married, three children French Organization: CNRS Laboratory: Gipsa-lab, Grenoble,

More information

Exponential Control Barrier Functions for Enforcing High Relative-Degree Safety-Critical Constraints

Exponential Control Barrier Functions for Enforcing High Relative-Degree Safety-Critical Constraints Exponential Control Barrier Functions or Enorcing High Relative-Degree Saety-Critical Constraints Quan Nguyen and Koushil Sreenath Abstract We introduce Exponential Control Barrier Functions as means to

More information

Formulations of Model Predictive Control. Dipartimento di Elettronica e Informazione

Formulations of Model Predictive Control. Dipartimento di Elettronica e Informazione Formulations of Model Predictive Control Riccardo Scattolini Riccardo Scattolini Dipartimento di Elettronica e Informazione Impulse and step response models 2 At the beginning of the 80, the early formulations

More information

PID Control. 6.1 Introduction

PID Control. 6.1 Introduction 6 PID Control 6. Introduction The PID controller is the most common form of feedback. It was an essential element of early governors and it became the standard tool when process control emerged in the

More information

Sampled-Data Model Predictive Control for Constrained Continuous Time Systems

Sampled-Data Model Predictive Control for Constrained Continuous Time Systems Sampled-Data Model Predictive Control for Constrained Continuous Time Systems Rolf Findeisen, Tobias Raff, and Frank Allgöwer Institute for Systems Theory and Automatic Control, University of Stuttgart,

More information

ECE 516: System Control Engineering

ECE 516: System Control Engineering ECE 516: System Control Engineering This course focuses on the analysis and design of systems control. This course will introduce time-domain systems dynamic control fundamentals and their design issues

More information

CSEN301 Embedded Systems Trimester 1

CSEN301 Embedded Systems Trimester 1 Victoria University of Wellington (VUW) course offering for NZ-EU Joint Mobility Project Novel Sensing Technologies and Instrumentation in Environmental Climate Change Monitoring 1. General The Victoria

More information

19 LINEAR QUADRATIC REGULATOR

19 LINEAR QUADRATIC REGULATOR 19 LINEAR QUADRATIC REGULATOR 19.1 Introduction The simple form of loopshaping in scalar systems does not extend directly to multivariable (MIMO) plants, which are characterized by transfer matrices instead

More information

Positive Feedback and Oscillators

Positive Feedback and Oscillators Physics 3330 Experiment #6 Fall 1999 Positive Feedback and Oscillators Purpose In this experiment we will study how spontaneous oscillations may be caused by positive feedback. You will construct an active

More information

Delay Impulsive Systems: A Model For NCSs. Motivation

Delay Impulsive Systems: A Model For NCSs. Motivation Center for Control, Dynamical-systems, and Computation University of California at Santa Barbara Impulsive Systems: A Model For NCSs Payam Naghshtabrizi Joao espanha 44 th Allerton Conference on Communication,

More information

DYNAMICAL NETWORKS: structural analysis and synthesis

DYNAMICAL NETWORKS: structural analysis and synthesis A social networks synchronization DYNAMICAL NETWORKS: structural analysis and synthesis traffic management B C (bio)chemical processes water distribution networks biological systems, ecosystems production

More information

Elgersburg Workshop 2010, 1.-4. März 2010 1. Path-Following for Nonlinear Systems Subject to Constraints Timm Faulwasser

Elgersburg Workshop 2010, 1.-4. März 2010 1. Path-Following for Nonlinear Systems Subject to Constraints Timm Faulwasser #96230155 2010 Photos.com, ein Unternehmensbereich von Getty Images. Alle Rechte vorbehalten. Steering a Car as a Control Problem Path-Following for Nonlinear Systems Subject to Constraints Chair for Systems

More information

Nonlinear normal modes of three degree of freedom mechanical oscillator

Nonlinear normal modes of three degree of freedom mechanical oscillator Mechanics and Mechanical Engineering Vol. 15, No. 2 (2011) 117 124 c Technical University of Lodz Nonlinear normal modes of three degree of freedom mechanical oscillator Marian Perlikowski Department of

More information

Proceeding of 5th International Mechanical Engineering Forum 2012 June 20th 2012 June 22nd 2012, Prague, Czech Republic

Proceeding of 5th International Mechanical Engineering Forum 2012 June 20th 2012 June 22nd 2012, Prague, Czech Republic Modeling of the Two Dimensional Inverted Pendulum in MATLAB/Simulink M. Arda, H. Kuşçu Department of Mechanical Engineering, Faculty of Engineering and Architecture, Trakya University, Edirne, Turkey.

More information

Tadahiro Yasuda. Introduction. Overview of Criterion D200. Feature Article

Tadahiro Yasuda. Introduction. Overview of Criterion D200. Feature Article F e a t u r e A r t i c l e Feature Article Development of a High Accuracy, Fast Response Mass Flow Module Utilizing Pressure Measurement with a Laminar Flow Element (Resistive Element) Criterion D200

More information

Lyapunov Stability Analysis of Energy Constraint for Intelligent Home Energy Management System

Lyapunov Stability Analysis of Energy Constraint for Intelligent Home Energy Management System JAIST Reposi https://dspace.j Title Lyapunov stability analysis for intelligent home energy of energ manageme Author(s)Umer, Saher; Tan, Yasuo; Lim, Azman Citation IEICE Technical Report on Ubiquitous

More information

OPERATIONAL AMPLIFIERS. o/p

OPERATIONAL AMPLIFIERS. o/p OPERATIONAL AMPLIFIERS 1. If the input to the circuit of figure is a sine wave the output will be i/p o/p a. A half wave rectified sine wave b. A fullwave rectified sine wave c. A triangular wave d. A

More information

SAMPLE CHAPTERS UNESCO EOLSS PID CONTROL. Araki M. Kyoto University, Japan

SAMPLE CHAPTERS UNESCO EOLSS PID CONTROL. Araki M. Kyoto University, Japan PID CONTROL Araki M. Kyoto University, Japan Keywords: feedback control, proportional, integral, derivative, reaction curve, process with self-regulation, integrating process, process model, steady-state

More information

Onboard electronics of UAVs

Onboard electronics of UAVs AARMS Vol. 5, No. 2 (2006) 237 243 TECHNOLOGY Onboard electronics of UAVs ANTAL TURÓCZI, IMRE MAKKAY Department of Electronic Warfare, Miklós Zrínyi National Defence University, Budapest, Hungary Recent

More information

ElastMan: Autonomic Elasticity Manager for Cloud-Based Key-Value Stores

ElastMan: Autonomic Elasticity Manager for Cloud-Based Key-Value Stores ElastMan: Autonomic Elasticity Manager for Cloud-Based Key-Value Stores Ahmad Al-Shishtawy KTH Royal Institute of Technology Stockholm, Sweden Doctoral School Day in Cloud Computing Louvain-la-Neuve, Belgium,

More information

Design-Simulation-Optimization Package for a Generic 6-DOF Manipulator with a Spherical Wrist

Design-Simulation-Optimization Package for a Generic 6-DOF Manipulator with a Spherical Wrist Design-Simulation-Optimization Package for a Generic 6-DOF Manipulator with a Spherical Wrist MHER GRIGORIAN, TAREK SOBH Department of Computer Science and Engineering, U. of Bridgeport, USA ABSTRACT Robot

More information

Peradeniya, Peradeniya 20400, Sri Lanka. E-mail: sanath@ee.pdn.ac.lk. Royal Institute of Technology, 100 44 Stockholm, Sweden.

Peradeniya, Peradeniya 20400, Sri Lanka. E-mail: sanath@ee.pdn.ac.lk. Royal Institute of Technology, 100 44 Stockholm, Sweden. REMOTE MONITORING AND DISTRIBUTED REAL-TIME CONTROL VIA ETHERNET SANATH ALAHAKOON 1, LILANTHA SAMARANAYAKE 2, THILAKASIRI VIJAYANANDA 1, MATS LEKSELL 2 1 Dept. of Electrical and Electronic Engineering,

More information

CONTRIBUTIONS TO THE AUTOMATIC CONTROL OF AERIAL VEHICLES

CONTRIBUTIONS TO THE AUTOMATIC CONTROL OF AERIAL VEHICLES 1 / 23 CONTRIBUTIONS TO THE AUTOMATIC CONTROL OF AERIAL VEHICLES MINH DUC HUA 1 1 INRIA Sophia Antipolis, AROBAS team I3S-CNRS Sophia Antipolis, CONDOR team Project ANR SCUAV Supervisors: Pascal MORIN,

More information

Robust output feedbackstabilization via risk-sensitive control

Robust output feedbackstabilization via risk-sensitive control Automatica 38 22) 945 955 www.elsevier.com/locate/automatica Robust output feedbackstabilization via risk-sensitive control Valery A. Ugrinovskii, Ian R. Petersen School of Electrical Engineering, Australian

More information

Matlab and Simulink. Matlab and Simulink for Control

Matlab and Simulink. Matlab and Simulink for Control Matlab and Simulink for Control Automatica I (Laboratorio) 1/78 Matlab and Simulink CACSD 2/78 Matlab and Simulink for Control Matlab introduction Simulink introduction Control Issues Recall Matlab design

More information

MODELING, SIMULATION AND DESIGN OF CONTROL CIRCUIT FOR FLEXIBLE ENERGY SYSTEM IN MATLAB&SIMULINK

MODELING, SIMULATION AND DESIGN OF CONTROL CIRCUIT FOR FLEXIBLE ENERGY SYSTEM IN MATLAB&SIMULINK MODELING, SIMULATION AND DESIGN OF CONTROL CIRCUIT FOR FLEXIBLE ENERGY SYSTEM IN MATLAB&SIMULINK M. Pies, S. Ozana VSB-Technical University of Ostrava Faculty of Electrotechnical Engineering and Computer

More information

Loop Analysis. Chapter 7. 7.1 Introduction

Loop Analysis. Chapter 7. 7.1 Introduction Chapter 7 Loop Analysis Quotation Authors, citation. This chapter describes how stability and robustness can be determined by investigating how sinusoidal signals propagate around the feedback loop. The

More information

DURING automatic vehicle following, the control objective

DURING automatic vehicle following, the control objective IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 48, NO. 1, JANUARY 1999 319 Autonomous Intelligent Cruise Control Using Front and Back Information for Tight Vehicle Following Maneuvers Y. Zhang, Elias

More information

Control System Definition

Control System Definition Control System Definition A control system consist of subsytems and processes (or plants) assembled for the purpose of controlling the outputs of the process. For example, a furnace produces heat as a

More information

Figure 1. The Ball and Beam System.

Figure 1. The Ball and Beam System. BALL AND BEAM : Basics Peter Wellstead: control systems principles.co.uk ABSTRACT: This is one of a series of white papers on systems modelling, analysis and control, prepared by Control Systems Principles.co.uk

More information

Chapter 7 Robust Stabilization and Disturbance Attenuation of Switched Linear Parameter-Varying Systems in Discrete Time

Chapter 7 Robust Stabilization and Disturbance Attenuation of Switched Linear Parameter-Varying Systems in Discrete Time Chapter 7 Robust Stabilization and Disturbance Attenuation of Switched Linear Parameter-Varying Systems in Discrete Time Ji-Woong Lee and Geir E. Dullerud Abstract Nonconservative analysis of discrete-time

More information

PID control - Simple tuning methods

PID control - Simple tuning methods - Simple tuning methods Ulf Holmberg Introduction Lab processes Control System Dynamical System Step response model Self-oscillation model PID structure Step response method (Ziegler-Nichols) Self-oscillation

More information

Lecture notes for the course Advanced Control of Industrial Processes. Morten Hovd Institutt for Teknisk Kybernetikk, NTNU

Lecture notes for the course Advanced Control of Industrial Processes. Morten Hovd Institutt for Teknisk Kybernetikk, NTNU Lecture notes for the course Advanced Control of Industrial Processes Morten Hovd Institutt for Teknisk Kybernetikk, NTNU November 3, 2009 2 Contents 1 Introduction 9 1.1 Scope of note..............................

More information

Op-Amp Simulation EE/CS 5720/6720. Read Chapter 5 in Johns & Martin before you begin this assignment.

Op-Amp Simulation EE/CS 5720/6720. Read Chapter 5 in Johns & Martin before you begin this assignment. Op-Amp Simulation EE/CS 5720/6720 Read Chapter 5 in Johns & Martin before you begin this assignment. This assignment will take you through the simulation and basic characterization of a simple operational

More information

PROCESS CONTROL DESCRIPTION OF THE UNITS

PROCESS CONTROL DESCRIPTION OF THE UNITS PROCESS CONTROL This article shows how complex control objectives were satisfied using powerful features attached to the regular multivariable predictive controller. The control objectives and results

More information

Laboratory 4: Feedback and Compensation

Laboratory 4: Feedback and Compensation Laboratory 4: Feedback and Compensation To be performed during Week 9 (Oct. 20-24) and Week 10 (Oct. 27-31) Due Week 11 (Nov. 3-7) 1 Pre-Lab This Pre-Lab should be completed before attending your regular

More information

Improving proposal evaluation process with the help of vendor performance feedback and stochastic optimal control

Improving proposal evaluation process with the help of vendor performance feedback and stochastic optimal control Improving proposal evaluation process with the help of vendor performance feedback and stochastic optimal control Sam Adhikari ABSTRACT Proposal evaluation process involves determining the best value in

More information

CONTROL SYSTEMS, ROBOTICS, AND AUTOMATION - Vol. I - Basic Elements of Control Systems - Ganti Prasada Rao

CONTROL SYSTEMS, ROBOTICS, AND AUTOMATION - Vol. I - Basic Elements of Control Systems - Ganti Prasada Rao BASIC ELEMENTS OF CONTROL SYSTEMS Ganti Prasada Rao International Centre for Water and Energy Systems, Abu Dhabi, UAE Keywords: Systems, Block diagram, Controller, Feedback, Open-loop control, Closedloop

More information

Lecture 27: Mixers. Gilbert Cell

Lecture 27: Mixers. Gilbert Cell Whites, EE 322 Lecture 27 Page 1 of 9 Lecture 27: Mixers. Gilbert Cell Mixers shift the frequency spectrum of an input signal. This is an essential component in electrical communications (wireless or otherwise)

More information

www.ncl.ac.uk/marine Module Content:

www.ncl.ac.uk/marine Module Content: Marine Project Management at is the largest and This module aims to introduce students to the key elements of up to date marine project management, including the application of work breakdown structures,

More information

Adaptive cruise controller design: a comparative assessment for PWA systems

Adaptive cruise controller design: a comparative assessment for PWA systems Adaptive cruise controller design: a comparative assessment for PWA systems Hybrid control problems for vehicle dynamics and engine control. Cagliari, PhD Course on discrete event and hybrid systems Daniele

More information

itesla Project Innovative Tools for Electrical System Security within Large Areas

itesla Project Innovative Tools for Electrical System Security within Large Areas itesla Project Innovative Tools for Electrical System Security within Large Areas Samir ISSAD RTE France samir.issad@rte-france.com PSCC 2014 Panel Session 22/08/2014 Advanced data-driven modeling techniques

More information

Microcontroller-based experiments for a control systems course in electrical engineering technology

Microcontroller-based experiments for a control systems course in electrical engineering technology Microcontroller-based experiments for a control systems course in electrical engineering technology Albert Lozano-Nieto Penn State University, Wilkes-Barre Campus, Lehman, PA, USA E-mail: AXL17@psu.edu

More information

System Modeling and Control for Mechanical Engineers

System Modeling and Control for Mechanical Engineers Session 1655 System Modeling and Control for Mechanical Engineers Hugh Jack, Associate Professor Padnos School of Engineering Grand Valley State University Grand Rapids, MI email: jackh@gvsu.edu Abstract

More information

Organization: Prof J. M. Balthazar (ACIESP, ITA, ABCM), Prof. L. C. S. Goes (ITA,ABCM), Prof. A.

Organization: Prof J. M. Balthazar (ACIESP, ITA, ABCM), Prof. L. C. S. Goes (ITA,ABCM), Prof. A. Organization: Prof J. M. Balthazar (ACIESP, ITA, ABCM), Prof. L. C. S. Goes (ITA,ABCM), Prof. A. Nabarrete (ITA), Dr. C. Oliveira (Post doctorate, ITA) and Prof. G.Litak (Lublin University of Technology

More information

IN-FLIGHT CALIBRATION OF THE MICROSCOPE SPACE MISSION INSTRUMENT: DEVELOPMENT OF THE SIMULATOR

IN-FLIGHT CALIBRATION OF THE MICROSCOPE SPACE MISSION INSTRUMENT: DEVELOPMENT OF THE SIMULATOR SF2A 2011 G. Alecian, K. Belkacem, R. Samadi and D. Valls-Gabaud (eds) IN-FLIGHT CALIBRATION OF THE MICROSCOPE SPACE MISSION INSTRUMENT: DEVELOPMENT OF THE SIMULATOR E. Hardy 1, A. Levy 1, G. Métris 2,

More information

The Filtered-x LMS Algorithm

The Filtered-x LMS Algorithm The Filtered-x LMS Algorithm L. Håkansson Department of Telecommunications and Signal Processing, University of Karlskrona/Ronneby 372 25 Ronneby Sweden Adaptive filters are normally defined for problems

More information

OPEN LOOP CONTROL OF FLEXIBLE BEAM PERIODIC MOTION VIA FREQUENCY RESPONSE ANALYSIS

OPEN LOOP CONTROL OF FLEXIBLE BEAM PERIODIC MOTION VIA FREQUENCY RESPONSE ANALYSIS ABCM Symposium Series in Mechatronics - Vol. 4 - pp.7-78 Copyright Proceedings 2 of COBEM by ABCM 29 Copyright c 29 by ABCM 2th International Congress of Mechanical Engineering November 5-2, 29, Gramado,

More information

Precise Modelling of a Gantry Crane System Including Friction, 3D Angular Swing and Hoisting Cable Flexibility

Precise Modelling of a Gantry Crane System Including Friction, 3D Angular Swing and Hoisting Cable Flexibility Precise Modelling of a Gantry Crane System Including Friction, 3D Angular Swing and Hoisting Cable Flexibility Renuka V. S. & Abraham T Mathew Electrical Engineering Department, NIT Calicut E-mail : renuka_mee@nitc.ac.in,

More information

DIEF, Department of Engineering Enzo Ferrari University of Modena e Reggio Emilia Italy Online Trajectory Planning for robotic systems

DIEF, Department of Engineering Enzo Ferrari University of Modena e Reggio Emilia Italy Online Trajectory Planning for robotic systems DIEF, Department of Engineering Enzo Ferrari University of Modena e Reggio Emilia Italy Online Trajectory Planning for robotic systems Luigi Biagiotti Luigi Biagiotti luigi.biagiotti@unimore.it Introduction

More information

Definition 8.1 Two inequalities are equivalent if they have the same solution set. Add or Subtract the same value on both sides of the inequality.

Definition 8.1 Two inequalities are equivalent if they have the same solution set. Add or Subtract the same value on both sides of the inequality. 8 Inequalities Concepts: Equivalent Inequalities Linear and Nonlinear Inequalities Absolute Value Inequalities (Sections 4.6 and 1.1) 8.1 Equivalent Inequalities Definition 8.1 Two inequalities are equivalent

More information

Non Linear Control of a Distributed Solar Field

Non Linear Control of a Distributed Solar Field Non Linear Control of a Distributed Solar Field Rui Neves-Silva rns@fct.unl.pt Universidade Nova de Lisboa ACUREX Solar Field 2 Parabolic through collector 3 Solar plant scheme The action on the pump s

More information

Designing Fluctronic Real-Time Systems

Designing Fluctronic Real-Time Systems Journal of Real-Time Systems, Special Issue on Control-Theoretical Approaches to Real-Time Computing Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms * Chenyang Lu John A. Stankovic

More information

System functions, requirements and resources

System functions, requirements and resources System functions, requirements and resources In this chapter, we examine the kind of functions systems can have. We also look at how requirements are generated, and how we should deal with resources. 1

More information

Implementation of Fuzzy and PID Controller to Water Level System using LabView

Implementation of Fuzzy and PID Controller to Water Level System using LabView Implementation of Fuzzy and PID Controller to Water Level System using LabView Laith Abed Sabri, Ph.D University of Baghdad AL-Khwarizmi college of Engineering Hussein Ahmed AL-Mshat University of Baghdad

More information

SERVO CONTROL SYSTEMS 1: DC Servomechanisms

SERVO CONTROL SYSTEMS 1: DC Servomechanisms Servo Control Sstems : DC Servomechanisms SERVO CONTROL SYSTEMS : DC Servomechanisms Elke Laubwald: Visiting Consultant, control sstems principles.co.uk ABSTRACT: This is one of a series of white papers

More information

Content. Professur für Steuerung, Regelung und Systemdynamik. Lecture: Vehicle Dynamics Tutor: T. Wey Date: 01.01.08, 20:11:52

Content. Professur für Steuerung, Regelung und Systemdynamik. Lecture: Vehicle Dynamics Tutor: T. Wey Date: 01.01.08, 20:11:52 1 Content Overview 1. Basics on Signal Analysis 2. System Theory 3. Vehicle Dynamics Modeling 4. Active Chassis Control Systems 5. Signals & Systems 6. Statistical System Analysis 7. Filtering 8. Modeling,

More information

Mobile Networking Tutorial

Mobile Networking Tutorial Dynamically Managing the Real-time Fabric of a Wireless Sensor-Actuator Network Award No: CNS-09-31195 Duration: Sept. 1 2009 - Aug. 31 2012 M.D. Lemmon, Univ. of Notre Dame (PI) S.X. Hu, Univ. of Notre

More information