Nonlinear Model-based Process Control: Applications in Petroleum Refining

247 Pages·2000·7.97 MB·English

by  Rashid M. Ansari PhD

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.