Practical Process Control for Engineers and Technicians Dedication This book is dedicated to Wolfgang who fought a courageous battle against motor neurone disease and continued teaching until the very end. Although he received his training in Europe, he ended up being one of Australia’s most outstanding instructors in industrial process control and inspired IDC Technologies into running his course throughout the world. His delight in taking the most complex control system problems and reducing them to simple practical solutions made him a sought after instructor in the process control field and an outstanding mentor to the IDC Technologies engineers teaching the topic. Hambani Kahle (Zulu Farewell) (Sources: Canciones de Nuestra Cabana (1980), Tent and Trail Songs (American Camping Association), Songs to Sing & Sing Again by Shelley Gorden) Go well and safely. Go well and safely. Go well and safely. The Lord be ever with you. Stay well and safely. Stay well and safely. Stay well and safely. The Lord be ever with you. Hambani Kahle. Hambani Kahle. Hambani Kahle. The Lord be ever with you. ii Contents Practical Process Control for Engineers and Technicians Wolfgang Altmann Dipl.Ing Contributing author: David Macdonald BSc (Hons) Inst. Eng, Senior Engineer, IDC Technologies, Cape Town, South Africa Series editor: Steve Mackay FIE (Aust), CPEng, BSc (ElecEng), BSc (Hons), MBA, Gov.Cert.Comp., Technical Director – IDC Technologies Pty Ltd AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Newnes is an imprint of Elsevier For information on all Newnes publications visit our website at www.newnespress.com Newnes An imprint of Elsevier Linacre House, Jordan Hill, Oxford OX2 8DP 30 Corporate Drive, Burlington, MA 01803 First published 2005 Copyright © 2005, IDC Technologies. All rights reserved No part of this publication may be reproduced in any material form (including photocopying or storing in any medium by electronic means and whether or not transiently or incidentally to some other use of this publication) without the written permission of the copyright holder except in accordance with the provisions of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London, England W1T 4LP. Applications for the copyright holder’s written permission to reproduce any part of this publication should be addressed to the publishers British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication Data A catalogue record for this book is available from the Library of Congress ISBN 0 7506 6400 2 Typeset by Integra Software Services Pvt. Ltd, Pondicherry, India www.integra-india.com Printed and bound in The Netherlands Working together to grow libraries in developing countries www.elsevier.com | www.bookaid.org | www.sabre.org Contents Preface xi 1 Introduction . 1 1.1 Objectives . 1 1.2 Introduction 1 1.3 Basic definitions and terms used in process control . 2 1.4 Process modeling . 2 1.5 Process dynamics and time constants 5 1.6 Types or modes of operation of process control systems . 13 1.7 Closed loop controller and process gain calculations . 15 1.8 Proportional, integral and derivative control modes 16 1.9 An introduction to cascade control 16 2 Process measurement and transducers 18 2.1 Objectives 18 2.2 The definition of transducers and sensors 18 2.3 Listing of common measured variables 18 2.4 The common characteristics of transducers . 19 2.5 Sensor dynamics 21 2.6 Selection of sensing devices 21 2.7 Temperature sensors . 22 2.8 Pressure transmitters . 28 2.9 Flow meters 35 2.10 Level transmitters . 42 2.11 The spectrum of user models in measuring transducers . 44 2.12 Instrumentation and transducer considerations 45 2.13 Selection criteria and considerations 48 2.14 Introduction to the smart transmitter . 50 3 Basic principles of control valves and actuators . 52 3.1 Objectives 52 3.2 An overview of eight of the most basic types of control valves 52 3.3 Control valve gain, characteristics, distortion and rangeability 67 3.4 Control valve actuators . 71 3.5 Control valve positioners 76 3.6 Valve sizing 76 vi Contents 4 Fundamentals of control systems 78 4.1 Objectives . 78 4.2 On–off control . 78 4.3 Modulating control 79 4.4 Open loop control . 79 4.5 Closed loop control . 81 4.6 Deadtime processes . 84 4.7 Process responses . 85 4.8 Dead zone 86 5 Stability and control modes of closed loops . 87 5.1 Objectives . 87 5.2 The industrial process in practice 87 5.3 Dynamic behavior of the feed heater 88 5.4 Major disturbances of the feed heater . 88 5.5 Stability . 89 5.6 Proportional control . 90 5.7 Integral control 93 5.8 Derivative control 95 5.9 Proportional, integral and derivative modes 98 5.10 I.S.A vs ‘Allen Bradley’ 98 5.11 P, I and D relationships and related interactions . 98 5.12 Applications of process control modes 99 5.13 Typical PID controller outputs . 99 6 Digital control principles . 100 6.1 Objectives . 100 6.2 Digital vs analog: a revision of their definitions 100 6.3 Action in digital control loops 100 6.4 Identifying functions in the frequency domain . 101 6.5 The need for digital control . 103 6.6 Scanned calculations 105 6.7 Proportional control . 105 6.8 Integral control 105 6.9 Derivative control 106 6.10 Lead function as derivative control 106 6.11 Example of incremental form (Siemens S5-100 V) . 107 7 Real and ideal PID controllers 108 7.1 Objectives . 108 7.2 Comparative descriptions of real and ideal controllers 108 7.3 Description of the ideal or the non-interactive PID controller . 108 7.4 Description of the real (Interactive) PID controller . 109 7.5 Lead function – derivative control with filter 110 7.6 Derivative action and effects of noise . 110 7.7 Example of the KENT K90 controllers PID algorithms . 111 Contents vii 8 Tuning of PID controllers in both open and closed loop control systems 112 8.1 Objectives 112 8.2 Objectives of tuning 112 8.3 Reaction curve method (Ziegler–Nichols) 114 8.4 Ziegler–Nichols open loop tuning method (1) 116 8.5 Ziegler–Nichols open loop method (2) using POI 117 8.6 Loop time constant (LTC) method 119 8.7 Hysteresis problems that may be encountered in open loop tuning 120 8.8 Continuous cycling method (Ziegler–Nichols) 120 8.9 Damped cycling tuning method 123 8.10 Tuning for no overshoot on start-up (Pessen) 126 8.11 Tuning for some overshoot on start-up (Pessen) . 127 8.12 Summary of important closed loop tuning algorithms 127 8.13 PID equations: dependent and independent gains . 127 9 Controller output modes, operating equations and cascade control . 131 9.1 Objectives 131 9.2 Controller output . 131 9.3 Multiple controller outputs . 132 9.4 Saturation and non-saturation of output limits . 133 9.5 Cascade control . 134 9.6 Initialization of a cascade system . 136 9.7 Equations relating to controller configurations 136 9.8 Application notes on the use of equation types . 139 9.9 Tuning of a cascade control loop 140 9.10 Cascade control with multiple secondaries . 141 10 Concepts and applications of feedforward control 142 10.1 Objectives 142 10.2 Application and definition of feedforward control . 142 10.3 Manual feedforward control 143 10.4 Automatic feedforward control 143 10.5 Examples of feedforward controllers . 144 10.6 Time matching as feedforward control 144 11 Combined feedback and feedforward control . 147 11.1 Objectives 147 11.2 The feedforward concept 147 11.3 The feedback concept 147 11.4 Combining feedback and feedforward control . 148 11.5 Feedback–feedforward summer . 148 11.6 Initialization of a combined feedback and feedforward control system 149 11.7 Tuning aspects . 149 12 Long process deadtime in closed loop control and the Smith Predictor 150 12.1 Objectives 150 12.2 Process deadtime . 150 viii Contents 12.3 An example of process deadtime 151 12.4 The Smith Predictor model . 152 12.5 The Smith Predictor in theoretical use 153 12.6 The Smith Predictor in reality 153 12.7 An exercise in deadtime compensation . 154 13 Basic principles of fuzzy logic and neural networks 155 13.1 Objectives . 155 13.2 Introduction to fuzzy logic . 155 13.3 What is fuzzy logic? . 156 13.4 What does fuzzy logic do? . 156 13.5 The rules of fuzzy logic . 156 13.6 Fuzzy logic example using five rules and patches 158 13.7 The Achilles heel of fuzzy logic . 159 13.8 Neural networks 159 13.9 Neural back propagation networking . 161 13.10 Training a neuron network 162 13.11 Conclusions and then the next step 163 14 Self-tuning intelligent control and statistical process control . 165 14.1 Objectives . 165 14.2 Self-tuning controllers . 165 14.3 Gain scheduling controller 166 14.4 Implementation requirements for self-tuning controllers 167 14.5 Statistical process control (SPC) 167 14.6 Two ways to improve a production process 168 14.7 Obtaining the information required for SPC 169 14.8 Calculating control limits . 173 14.9 The logic behind control charts . 175 Appendix A: Some Laplace transform pairs . 176 Appendix B: Block diagram transformation theorems . 179 Appendix C: Detail display . 181 Appendix D: Auxiliary display . 185 Appendix E: Configuring a tuning exercise in a controller 188 Appendix F: Installation of simulation software 190 Appendix G: Operation of simulation software . 193 Appendix H: Configuration . 197 Appendix I: General syntax of configuration commands 198 Contents ix Appendix J: Configuration commands . 199 Appendix K: Algorithms . 208 Appendix L: Background graphics design 223 Appendix M: Configuration example 224 Introduction to exercises 229 Exercise 1: Flow control loop – basic example . 231 Exercise 2: Proportional (P) control– flow chart 234 Exercise 3: Integral (I) Control – flow control 237 Exercise 4: Proportional and integral (PI) control – flow control . 240 Exercise 5: Introduction to derivative (D) control 242 Exercise 6: Practical introduction into stability aspects . 246 Exercise 7: Open loop method – tuning exercise . 252 Exercise 8: Closed loop method – tuning exercise . 256 Exercise 9: Saturation and non-saturation output limits 260 Exercise 10: Ideal derivative action – ideal PID 263 Exercise 11: Cascade control 267 Exercise 12: Cascade control with one primary and two secondaries 271 Exercise 13: Combined feedback and feedforward control 276 Exercise 14: Deadtime compensation in feedback control . 279 Exercise 15: Static value alarm 284 Index . 286 . available. 2 Practical Process Control for Engineers and Technicians 1.3 Basic definitions and terms used in process control Most basic process control systems. factor in the response and in the control loop tuning. 6 Practical Process Control for Engineers and Technicians 1.5.1 First order process dynamic characteristics