Advances in Industrial Control Springer London Berlin Heidelberg New York Barcelona Hong Kong Milan Paris Singapore Tokyo Other titles published in this Series: Modelling and Simulation ofH uman Behaviour in System Control Pietro Carlo Cacciabue Modelling and Identification in Robotics Krzysztof Kozlowski Spacecraft Navigation and Guidance Maxwell Noton Robust Estimation and Failure Detection Rami Mangoubi Adaptive Internal Model Control Aniruddha Datta Price-Based Commitment Decisions in the Electricity Market Erie Allen and Marija Ilie Compressor Surge and Rotating Stall: Modeling and Control Jan Tommy Gravdahl and Olav Egeland Radiotheraphy Treatment Planning: New System Approaches Olivier Haas Feedback Control Theory for Dynamic Traffic Assignment Pushkin Kachroo and Kaan 6zbay Control and Instrumentation for Wastewater Treatment Plants Reza Katebi, Michael A. Johnson & Jacqueline Wilkie Autotuning ofPID Controllers Cheng-Ching Yu Robust Aeroservoelastic Stability Analysis Rick Lind & Marty Brenner Performance Assessment of Control Loops:Theory and Applications Biao Huang & Sirish L. Shah Data Mining and Knowledge Discovery for Process Monitoring and Control XueZ. Wang Advances in PID Control Tan Kok Kiong, Wang Quing-Guo & Hang Chang Chieh with Tore J. Hagglund Advanced Control with Recurrent High-order Neural Networks: Theory and Industrial Applications George A. Rovithakis & Manolis A. Christodoulou Structure and Synthesis ofPID Controllers Aniruddha Datta, Ming-Tzu Ho and Shankar P. Bhattacharyya Data-driven Techniques for Fault Detection and Diagnosis in Chemical Processes Evan L. Russell, Leo H. Chiang and Richard D. Braatz Modelling and Control ofB ounded Dynamic Stochastic Distribution Hong Wang Rashid M. Ansari and Moses O. Tade Nonlinear Model-based Process Control Applications in Petroleum Refining With 83 Figures i Springer Rashid M. Ansari, PhD Department of Chemical Engineering, Curtin University of Technology, GPO Box U 1987, Perth 6845, Australia Moses O. Tade, PhD Department of Chemical Engineering, Curtin University of Technology, GPO Box U 1987, Perth 6845, Australia ISBN-13: 978-1-4471-1192-4 e-ISBN-13: 978-1-4471-0739-2 DOl: 10.1007/978-1-4471-0739-2 British Library Cataloguing in Publication Data Ansari, Rshid M. Nonlinear model-based process control: applications in petroleum refining. -(Advances in industrial control) I.Petroleum -Refining 2.Nonlinear control theory LTitle ILTade, Moses O. 629.8'36 Library of Congress Cataloging-in-Publication Data Ansari, Rashid. Nonlinear model-based process control: applications in petroleum refining! Rashid M. Ansari and Moses O. TaM. p. com --(Advances in industrial control) Includes bibliographical references. 1. Petroleum--Refining 2. Chemical process control. 3. Nonlinear control theory. I. Tade, Moses O. II. Title. III. Series. TP690.3 .AS7 2000 665.S'3--dc21 99-047343 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of repro graphic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. © Springer-Verlag London Limited 2000 Softcover reprint of the hardcover I st edition 2000 "MATLABo and is the registered trademark of The Math Works, Inc., http://www.mathworks.com. . The use of registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Typesetting: Camera ready by authors 69/3830-543210 Printed on acid-free paper SPIN 10731580 Advances in Industrial Control Series Editors Professor Michael J. Grimble, Professor of Industrial Systems and Director Professor Michael A. Johnson, Professor of Control Systems and Deputy Director Industrial Control Centre Department of Electronic and Electrical Engineering University of Strathclyde Graham Hills Building 50 George Street Glasgow GIl QE United Kingdom Series Advisory Board Professor Dr-Ing J. Ackermann DLR Institut fUr Robotik und Systemdynamik Postfach 1116 D82230 WeBiing Germany Professor J.D. Landau Laboratoire d'Automatique de Grenoble ENSIEG, BP 46 38402 Saint Martin d'Heres France Dr D.C. McFarlane Department of Engineering University of Cambridge Cambridge CB2 1QJ United Kingdom Professor B. Wittenmark Department of Automatic Control Lund Institute of Technology PO Box 118 S-221 00 Lund Sweden Professor D.W. Clarke Department of Engineering Science University of Oxford Parks Road Oxford OXl 3PJ United Kingdom Professor Dr -Ing M. Thoma Institut fur Regelungstechnik Universitat Hannover Appelstr. 11 30167 Hannover Germany Professor H. Kimura Department of Mathematical Engineering and Information Physics Faculty of Engineering The University ofTokyo 7-3-1 Hongo Bunkyo Ku Tokyo 113 Japan Professor A.J. Laub College of Engineering -Dean's Office University of California One Shields Avenue Davis California 95616-5294 United States of America Professor J.B. Moore Department of Systems Engineering The Australian National University Research School of Physical Sciences GPO Box 4 Canberra ACT 2601 Australia Dr M.K. Masten Texas Instruments 2309 N orthcrest Plano TX 75075 United States of America Professor Ton Backx AspenTech Europe B.V. DeWaal32 NL-5684 PH Best The Netherlands SERIES EDITORS' FOREWORD The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The last decade has seen considerable interest in reviving the fortunes of non linear control. In contrast to the approaches of the 60S, 70S and 80S a very pragmatic agenda for non-linear control is being pursued using the model-based predictive control paradigm. This text by R. Ansari and M. Tade gives an excellent synthesis of this new direction. Two strengths emphasized by the text are: (i) four applications found in refinery processes are used to give the text a firm practical continuity; (ii) a non-linear model-based control architecture is used to give the method a coherent theoretical framework. A key issue raised by this text concerns the ease with which realistic and accurate non-linear models can be generated for insertion into the non-linear model-based control architecture. The models for refinery processes have probably been reasonably well researched but many other areas may not be so fortunate. For example, non-linear bio-chemical reactors are one area in which it is difficult to devise phenomenologically based models, which have sufficient accuracy for control purposes. We feel that this text is thoroughly topical and will be of considerable interest to the academic control community and also to the industrial engineer. The latter is likely to be very interested in the degree of enhanced performance that non linear control can offer in real applications. M.J. Grimble and M.A. Johnson Industrial Control Centre Glasgow, Scotland, UK PREFACE The work in this book entails developing non-linear model-based multivariable control algorithms and strategies and utilizing an integrated approach of the control strategy, incorporating a process model, an inferential model and multivariable control algorithm in one framework. This integrated approach was applied to various refinery processes, which exhibit strong non-linearities, process interactions and constraints and has been shown to produce good results for a range of refinery processes by improving the closed-loop quality control and maximizing the yield of high-value products. This makes non-linear model-based multivariable control an attractive alternative to linear methods. The generic model control (GMC) structure of Lee and Sullivan (1988) was selected for this research and practical work in this book which permits the direct use of non-linear steady-state and dynamic models and, therefore, provides the basic structure of the model-based controller. The non-linear model-based control structure was further extended to permit the use of inferential models in non-linear multivariable control applications. A wide range of inferential models was developed, implemented in real-time and integrated with non-linear multi variable control applications. These inferential models demonstrate the improvement in the performance of closed-loop quality control and dynamic response of the system by reducing the long time delays. In order to demonstrate the effectiveness of non-linear model-based control with regards to industrial application, a non-linear control strategy was developed for an industrial debutanizer and implemented in real-time. The non-linear control provided improved control performance of the product qualities. A steady-state model of debutanizer with approximate dynamics was used in the control strategies. A complex multi variable control problem was solved by formulating the non linear constrained optimization strategy for a crude distillation process. The heavy oil fractionator problem proposed by Shell Oil was selected for this work. The method uses the non-linear model-based controller, which considers the model uncertainty explicitly. The method is based on formulating the constrained non linear optimization (NLP) programme that optimizes performance objectives subject to constraints. The model was built in MATLAB@/SIMULINK@ and the results were tested and compared with the results obtained from non-linear control techniques. A constrained non-linear multivariable control and optimization strategy for handling the constraints was proposed and applied in real time to a semiregenerative x Preface catalytic reforming reactor section. An octane inferential model was developed and integrated with non-linear multi variable controller forming a closed-loop W AIT/octane quality control. A dynamic model of the catalytic reforming process was developed and used in this control application on the reactor section to provide target values for the reactor inlet temperature. It was shown that constrained non linear multi variable control provided better disturbance rejection compared to traditional linear control. The optimization approach in this work provided a trade off between the process outputs tracking their reference trajectories and constraint violation. Finally a non-linear constrained optimization strategy was proposed and applied to a fluid catalytic cracking reactor-regenerator section using a simplified FCC process model. A dynamic parameter update algorithm was developed and used to reduce the effect of larger modelling errors by regularly updating the selected model parameters. The main advantage of the proposed non-linear controller development approach is that a single-time step control law resulted in a much smaller dimensional non-linear programme as compared to other previous methods. Since the same model was used for optimization and control, it minimized the maintenance and process re-identification efforts, which was required for linear controller development as the operating conditions change. One of the key objectives of the applied work in this book was to develop and implement in real-time the non-linear model-based multivariable control and constraint optimization algorithms on various refinery processes with strong non linearities and process interaction. The implementation of these strategies and techniques in real-time has demonstrated an improved control performance over linear control, emphasizing the need of a high-performance model-based non-linear multi variable control system. This book may serve as a concise reference for process control engineers interested in non-linear process control theory and applications. We tried to apply the non-linear control concepts and methods in real-time applications in petroleum refining industry and hope that the readers will find this book interesting and useful. Rashid M. Ansari Moses O. Tade ACKNOWLEDGEMENTS It was always my desire and ambition to write a book in the field of advanced process control. The realization of this ambition demands a greater commitment and dedication to complete the work. During the last year, I realized that my ambition to write a book in control area turned into a great challenge for me and I have accepted that challenge. However, my ambition would have never been realized without the help of the following people: I would like to express my sincerest gratitude to Dr. Moses O. Tade for his invaluable guidance, helpful advice and consistent encouragement throughout the duration of this work. I am especially grateful to his thorough reading of several drafts of this book and his valuable corrections. My sincere thanks to Professor Terry Smith for encouraging me to continue working in the field of advanced control and optimization. Many thanks to Dr. Weibiao Zhou and Dr. Peter L. Lee for their initial help in understanding the non-linear generic model control techniques. Thanks to my colleagues Ashraf A. AI-Ghazzawi and Dr. Talal Bakri for their help on setting up the MATLAB@/SIMULINK@control system. I am also grateful to Majed A. Intabi, Manager, Riyadh Refinery who always admired my work and extended his support for any professional activity, which can contribute to the development of young engineers. Special thanks to Editors of Saudi Aramco Journal of Technology for publishing some of my work in the technical journal and Oliver Jackson, Editorial Assistant of Springer-Verlag for his help in completing the write-up of this book.