Techniques for Adaptive Control Techniques for Adaptive Control Edited by Vance J. VanDoren, Ph.D., P.E. Consulting Editor, Control Engineering Magazine, Oak Brook, Illinois Amsterdam Boston London New York Oxford Paris San Diego San Francisco Singapore Sydney Tokyo Butterworth±Heinemann is an imprint of Elsevier Science. Copyright # 2003, Elsevier Science (USA). All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. ϱ Recognizing the importance of preserving what has been written, Elsevier Science prints its books on acid-free paper whenever possible. Library of Congress Cataloging-in-Publication Data Techniques for adaptive control / edited by Vance J. VanDoren. p. cm. Includes bibliographical references and index. ISBN 0-7506-7495-4 (pbk. : alk. paper) 1. Adaptive control systems. I. VanDoren, Vance J. TJ217 .T42 2002 629.8 H 36Ðdc21 2002074432 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. The publisher offers special discounts on bulk orders of this book. For information, please contact: Manager of Special Sales Elsevier Science 200 Wheeler Road Burlington, MA 01803 Tel: 781-313-4700 Fax: 781-313-4882 For information on all Butterworth±Heinemann publications available, contact our World Wide Web home page at: http://www.bh.com 10987654321 Printed in the United States of America Contributors . Preface . Introduction . Terminology . Contents Commercial adaptive controllers . Problems with PID . Advantages of adaptive control . Disadvantages of adaptive control . The ideal adaptive controller Basic concepts . Model-based techniques Modern alternatives . Curve-fitting challenges . More challenges Still more challenges Popular nonetheless A model-free technique Pros and cons Rule-based techniques Fuzzy logic . More pros and cons . Pick one . Usability . Assumptions Other considerations References 1 Adaptive tuning methods of the Foxboro I/A system . Controller structure Minimum variance control Control by minimizing sensitivity to process uncertainty Algebraic controller design for load rejection and shaped transient response . Algebraic tuning of a controller with deadtime Robust adaption of feedback controller gain scheduling Feedforward control . Adaption of feedforward load compensators Conclusion 1 References 1 . Suggested reading 1 2 The exploitation of adaptive modeling in the model predictive control of Connoisseur Model structures Issues for identification Adaptive modeling . Other methods . Simulated case study on a fluid catalytic cracking unit . Conclusion 2 References 2 . 3 Adaptive predictive regulartory control with Brainwave . The Laguerre modeling method . Building the adaptive predictive controller based on a Laguerre state space model . A Laguerre-based controller for integrating systems Practical issues for implementing adaptive predictive controllers . Simulation examples Industrial application examples Conclusions 3 Acknowledgements 3 . References 3 . 4 Model-free adaptive control with CyboCon Concept of MFA control . Single-loop MFA control system Multivariable MFA control system Anti-delay MFA control system MFA cascade control system . Feedforward MFA control Nonlinear MFA control . Robust MFA control . MFA control methodology and applications MFA control methodology The inside of MFA Case studies 4 . References 4 . Suggested reading 4 5 Expert-based adaptive control: Controlsoft’s Intune adaptive and diagnostic software . On-demand tuning and adaptive tuning . History and milestone literature . Adaptive control structure and underlying principles Identification-based adaptive control . Expert-based adaptive control: ControlSoft’s Intune . Concluding observations 5 References 5 . Intelligent software objects and their use in KnowledgeScope . Artificial intelligence and process control . Neural networks . Genetic algorithms . Documenting the performance of Intelligence Systems Putting it all together: combining intelligent technologies for process control Results: using intelligent control in the mineral-processing industry . Conclusion 6 References 6 . Appendix: table of artificial reference texts . Author index Subject index . CONTRIBUTORS George S. Cheng, Ph.D. President and Chief Technical Officer, CyboSoft, General Cybernation Group Inc., Rancho Cordova, California Tien-Li Chia, Ph.D. President, ControlSoft, Cleveland, Ohio Guy A. Dumont, Ph.D. Professor, Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada William A. Gough, P.Eng. Vice President, Universal Dynamics Technologies Inc., Richmond, British Columbia, Canada Kenneth S. Gritton, Ph.D. Director of Technology and Development, EIMCO Process Equipment Company, Salt Lake City, Utah Lynn B. Hales, B.S. General Manager, KnowledgeScape Systems, EIMCO Process Equipment Company, Salt Lake City, Utah Peter D. Hansen, B.S., M.S., Sc.D. Consultant, and Bristol Fellow (Retired), The Foxboro Co., Foxboro, Massachusetts Mihai Huzmezan, Ph.D., P.Eng. Assistant Professor, The University of British Columbia; President, MIH Consulting Group Ltd., Vancouver, Canada Irving Lefkowitz, Ph.D. Vice President, ControlSoft, Cleveland, Ohio David J. Sandoz, Ph.D. Director (Retired), Control Technology Centre Ltd., Manchester, United Kingdom viii . Techniques for Adaptive Control Techniques for Adaptive Control Edited by Vance J. VanDoren, Ph.D., P.E. Consulting Editor, Control Engineering. books on acid-free paper whenever possible. Library of Congress Cataloging-in-Publication Data Techniques for adaptive control / edited by Vance J. VanDoren.