PI Control. Chapter 7. Class 7. Overdamped Process Model Forms. Run Pumped Tank. Which One to Use? Self Regulating Overdamped Models

Similar documents
Lambda Tuning the Universal Method for PID Controllers in Process Control

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

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

PID Tuning Guide. A Best-Practices Approach to Understanding and Tuning PID Controllers. First Edition by Robert C. Rice, PhD

Understanding Poles and Zeros

Process Control Primer

stable response to load disturbances, e.g., an exothermic reaction.

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

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

Enhancing Process Control Education with the Control Station Training Simulator

Chapter 10. Key Ideas Correlation, Correlation Coefficient (r),

Jitter Measurements in Serial Data Signals

Process Dynamics, Operations, and Control Lecture Notes - 11 Lesson 11. Frequency response of dynamic systems.

1.3 LINEAR EQUATIONS IN TWO VARIABLES. Copyright Cengage Learning. All rights reserved.

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

Second Order Systems

EECE 460 : Control System Design

Module 3: Correlation and Covariance

PID Control. Chapter 10

Lecture - 4 Diode Rectifier Circuits

HITACHI INVERTER SJ/L100/300 SERIES PID CONTROL USERS GUIDE

Impedance Matching and Matching Networks. Valentin Todorow, December, 2009

Measurement Products. PID control theory made easy Optimising plant performance with modern process controllers

Understanding Power Impedance Supply for Optimum Decoupling

Chapter 10. Control Design: Intuition or Analysis?

Current Loop Tuning Procedure. Servo Drive Current Loop Tuning Procedure (intended for Analog input PWM output servo drives) General Procedure AN-015

Dynamic Process Modeling. Process Dynamics and Control

Sensing and Control. A Process Control Primer

Univariate Regression

Binary Adders: Half Adders and Full Adders

Industrial Steam System Process Control Schemes

SR2000 FREQUENCY MONITOR

Inrush Current. Although the concepts stated are universal, this application note was written specifically for Interpoint products.

Section 5.0 : Horn Physics. By Martin J. King, 6/29/08 Copyright 2008 by Martin J. King. All Rights Reserved.

Using SAS Proc Mixed for the Analysis of Clustered Longitudinal Data

X X X a) perfect linear correlation b) no correlation c) positive correlation (r = 1) (r = 0) (0 < r < 1)

MAS.836 HOW TO BIAS AN OP-AMP

PID Control. Proportional Integral Derivative (PID) Control. Matrix Multimedia 2011 MX009 - PID Control. by Ben Rowland, April 2011

Uses of Derivative Spectroscopy

Frequency Response of Filters

8. Time Series and Prediction

Doppler. Doppler. Doppler shift. Doppler Frequency. Doppler shift. Doppler shift. Chapter 19

Sample Size and Power in Clinical Trials

VCO Phase noise. Characterizing Phase Noise

Marine Technology Society

Module 13 : Measurements on Fiber Optic Systems

Fundamentals of Mass Flow Control

A Design of a PID Self-Tuning Controller Using LabVIEW

CBS RECORDS PROFESSIONAL SERIES CBS RECORDS CD-1 STANDARD TEST DISC

Best Practices for Controller Tuning

Alphasense Application Note AAN DESIGNING A POTENTIOSTATIC CIRCUIT

Measuring Line Edge Roughness: Fluctuations in Uncertainty

Thermal Conductivity Detector

DEALING WITH THE DATA An important assumption underlying statistical quality control is that their interpretation is based on normal distribution of t

CALCULATIONS & STATISTICS

The Standard Normal distribution

23 The Thermal Conductivity Detector

Entrained Gas Diagnostic with Intelligent Differential Pressure Transmitter

Phase-Locked Loop Based Clock Generators

Appendix D Digital Modulation and GMSK

The Precharge Calculator

SINGLE-SUPPLY OPERATION OF OPERATIONAL AMPLIFIERS

Advanced Signal Analysis Method to Evaluate the Laser Welding Quality

SPW3 Speed Programmed Winder. Application Handbook. Copyright 2000 by SSD Drives, Inc. Printed in the United States of America HA Issue 3

Operational Overview and Controls Guide

Linear functions Increasing Linear Functions. Decreasing Linear Functions

An Introduction to. Metrics. used during. Software Development

USB 3.0 CDR Model White Paper Revision 0.5

Agilent AN 1316 Optimizing Spectrum Analyzer Amplitude Accuracy

Energy Efficient Operations and Maintenance Strategies for Boilers

(Refer Slide Time: 00:01:16 min)

Counters and Decoders

Applying Pressure Independent Control Valves in H.V.A.C. Systems. A Presentation to: Orange Empire ASHRAE Santa Ana Nov. 17, 2009

CHAPTER 7: AGGREGATE DEMAND AND AGGREGATE SUPPLY

Application Note Noise Frequently Asked Questions

Additional sources Compilation of sources:

Formula for linear models. Prediction, extrapolation, significance test against zero slope.

Transmission Line and Back Loaded Horn Physics

Making Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz

Lock - in Amplifier and Applications

CENTRIFUGAL PUMP SELECTION, SIZING, AND INTERPRETATION OF PERFORMANCE CURVES

Basic Hydraulics and Pneumatics

Prelab Exercises: Hooke's Law and the Behavior of Springs

FTIR Instrumentation

Mixing Valves. ARGUS Application Note: Mixing Valves

Equipment: Power Supply, DAI, Synchronous motor (8241), Electrodynamometer (8960), Tachometer, Timing belt.

A More Efficient Way to De-shelve 137 Ba +

The Calculation of G rms

Pressure Relief and Regulating Valves

'Possibilities and Limitations in Software Defined Radio Design.

Time Series and Forecasting

Daily vs. monthly rebalanced leveraged funds

Math 1. Month Essential Questions Concepts/Skills/Standards Content Assessment Areas of Interaction

EDEXCEL NATIONAL CERTIFICATE/DIPLOMA UNIT 5 - ELECTRICAL AND ELECTRONIC PRINCIPLES NQF LEVEL 3 OUTCOME 4 - ALTERNATING CURRENT

Little LFO. Little LFO. User Manual. by Little IO Co.

TEA1024/ TEA1124. Zero Voltage Switch with Fixed Ramp. Description. Features. Block Diagram

Users Guide. By Dr. Don J. Wood Dr. Srinivasa Lingireddy. Featuring the Surge Wizard

Automatic compression measurement using network analyzers

PID Microprocessor temperature controllers CTD43 - CTD46 - CTH46

CPW Current Programmed Winder. Application Handbook. Copyright 2002 by Eurotherm Drives, Inc.

Transcription:

Chapter 7 1. What is the main point of this chapter? Class 7. This chapter describes the FOPDT model as a linear model. Clearly, the response is not linear with time. In what way is the model linear? PI Control 3. What is the difference between a self-regulating and non-self-regulating process? Qualitatively, sketch the response of each to a step change in input. Copyright 007 All Rights Reserved 1 Copyright 007 All Rights Reserved Run Pumped Tank Overdamped Process Model Forms Here we focus on the control of temperature, pressure, level, flow, density, concentration, etc. where the process streams are comprised of gases, liquids, slurries and melts These are overdamped processes because the is no natural tendency to oscillate In Manual Mode, change controller output They also tend to be self regulating because they seek a steady state operating level if all variables are held constant Copyright 007 All Rights Reserved 3 Copyright 007 All Rights Reserved 4 Self Regulating Overdamped Models First Order Plus Dead Time (FOPDT) τ P + y( = K P u( t θ P ) Constants 3 Which One to Use? One more adjustable parameter is better for data interpolation but makes it more risky to extrapolate beyond the bounds of the original data used to fit the model Second Order Plus Dead Time (SOPDT) d y( τ P1 τ P + ( τ 1 ) ( ) ( ) P + τ P + y t = K P u t θ P Second Order Plus Dead Time with Lead Time (SOPDT w/ L) d y( du( t θ P) τ P1τ P + ( τ P1 + τ P) + y( = KP u ( t θ P ) + τ 5 L 4 Choose the simplest model that fits of your data because it will provide the safest extrapolation Copyright 007 All Rights Reserved 5 Copyright 007 All Rights Reserved 6

The PI Controller Ideal form of the PI Controller CO= CO + e( + e( where: CO = controller output signal CO = controller or null value = measured process variable = set point e( = controller error = = controller gain (a tuning parameter) = controller reset time (a tuning parameter) is in denominator so smaller values provide a larger weighting to the integral term has units of time, and therefore is always positive Copyright 007 All Rights Reserved 7 Function of the Proportional Term e(40) = The proportional term, e(, immediately impacts CO based on the size of e( at a particular time t The past history and current trajectory of the controller error have no influence on the proportional term computation Copyright 007 All Rights Reserved 8 5 Proportional term acts on e( = All Rights Reserved 40 Control Calculation is Based on Error, e( Function of the Integral Term e(40) = Proportional term acts on e( = e( Same data plotted as controller error, e( The integral term continually sums up error, e( Through constant summing, integral action accumulates influence based on how long and how far the measured has been from over time. e(40) = 0 All Rights Reserved All Rights Reserved 5 40 5 40 Here is identical data plotted two ways To the right is a plot of error, where: e( = Error e( continually changes size and sign with time Even a small error, if it persists, will have a sum total that grows over time and the amount added to CO will similarly grow. The continual summing of integration starts from the moment the controller is put in automatic Copyright 007 All Rights Reserved 9 Copyright 007 All Rights Reserved 10 Integral Term Continually Sums the Value: Integral of Error is the Same as Integral of: Each box has integral sum of 0 ( high x 10 wide) Integral term continually sums e( = Integral term continually sums error, e( Integral sum = 34 Integral sum = 7 Integral sum = 135 Integral sum = 135 Integral sum = 34 Integral sum = 7 0 All Rights Reserved All Rights Reserved The integral is the sum of the area between and At t = 3 min, when the first reaches the, the integral is: 3min e( = 135 0min Copyright 007 All Rights Reserved 11 At t = 60 min, the total integral is: 135 34 = 101 When the dynamics have ended, e( is constant at zero and the total integral has a final residual value: 135 34 + 7 = 108 Copyright 007 All Rights Reserved 1

Advantage of PI Control No Offset The PI controller stops computing changes in CO when e( equals zero for a sustained period CO= CO + e( + e( At that point, the proportional term equals zero, and the integral term may have a residual value CO = CO + 0 + (108) 1443 Integral acts as moving term This residual value, when added to CO, essentially creates an overall moving that tracks changes in operating level This moving eliminates offset, making PI control the most widely used industry algorithm Disadvantages of PI Control - Interaction Integral action tends to increase the oscillatory or rolling behavior of the There are two tuning parameters ( and ) and they interact with each other CO= CO + e( + e( This interaction can make it challenging to arrive at best tuning values Copyright 007 All Rights Reserved 13 Copyright 007 All Rights Reserved 14 PI Controller Tuning Guide (Figure 8.9) Reset Time vs Reset Rate Base Case Performance Manufacturers confuse tuning and implementation by using different names and units for the same controller parameter: Some use proportional band (PB) instead of controller gain () Some use reset rate ( τ R ) instead of reset time ( ), where: 1 τ R = I τ Reset rate ( τ R ) has units of 1/time or sometimes repeats/minute / / Know your manufacturer before we start tuning a controller Copyright 007 All Rights Reserved 15 Copyright 007 All Rights Reserved 16 Integral Action and Reset Windup The math makes if possible for the error sum (the integral) to grow very large. CO= CO + e( + e( integral The integral term can grow so large that the total CO signal stops making sense (it can be signaling for a valve to be open 10% or negative 15%) Windup is when the CO grows to exceed the valve limits because the integral has reached a huge positive/negative value It is associated with the integral term, so it is called reset windup The controller can t regulate the process until the error changes sign and the integral term shrinks sufficiently so that the CO value again makes sense (moves between 0 100%). Reset Windup and Jacketing Logic Industrial controllers employ jacketing logic to halt integration when the CO reaches a maximum or minimum value Beware if you program your own controller because reset windup is a trap that novices fall into time and again If two controllers trade off regulation of a single (e.g. select control; override control), jacketing logic must instruct the inactive controller to stop integrating. Otherwise, that controller s integral term can wind up. Copyright 007 All Rights Reserved 17 Copyright 007 All Rights Reserved 18

Evaluating Controller Performance Bioreactors can t tolerate sudden operating changes because the fragile living cell cultures could die.» good control means moves slowly Packaging/filling stations can be unreliable. Upstream process must ramp back quickly if a container filling station goes down.» good control means moves quickly The operator or engineer defines what is good or best control performance based on their knowledge of: goals of production capabilities of the process impact on down stream units desires of management Many Performance Analysis Methods Classical Response to Set Point Step Analysis Rise Time Settling Time Peak Overshoot Ratio Diagnostic Measures Auto and Cross Correlation Power Spectrum (Spectral Density) Performance Monitoring Indexes (Use Moving Window) Moving Average Window Relative Variance and Standard Deviation Copyright 007 All Rights Reserved 19 Copyright 007 All Rights Reserved 0 Classical Analysis - Peak Related Criteria Classical Analysis - Peak Related Criteria A=(30 0) = 10% B = (34.5 30) =4.5% C=(31 30) =1% Peak Overshoot Ratio (POR) = B/A Decay Ratio = C/B Here: POR = 4.5/10 = 0.45 or 45% Decay ratio = 1/4.5 = 0. or % Copyright 007 All Rights Reserved 1 Copyright 007 All Rights Reserved Classical Analysis - Time Related Criteria Classical Analysis - Time Related Criteria peak time The clock for time related events begins when the is stepped peak time t rise = 43 30 = 13 min t peak = 51 30 = 13 min t settle = 100 30 = 70 min Copyright 007 All Rights Reserved 3 Copyright 007 All Rights Reserved 4

Classical Analysis Note Classical Analysis What If No Peaks? The classical criteria are not independent: if decay ratio is large, then likely will have a long settling time if is long, then likely will have a long peak time peak time Old rule-of-thumb is to design for a 10% POR and/or a 5% decay ratio (called a quarter decay) Yet many modern operations want no overshoot at all, making B = C = 0 With no peaks, the classical criteria are of limited value Copyright 007 All Rights Reserved 5 Copyright 007 All Rights Reserved 6 Settling Time Doesn t Use Peaks But is Noise Specific ±0% of Settling time is the time it takes for the to enter and remain within a band of operation - no peaks required A process with more noise must have a wider settling band Copyright 007 All Rights Reserved 7