模型预测控制学习实用教材

【实例简介】
模型预测控制学习实用教材
Other titles published in this series Digital Controller implementation Modelling and Control of Mini- Flying d fragility Mach Robert s.h. Istepanian and James F Pedro castillo. Rogelio lozano Whidborne(eds) and Alejandro dzul Optimisation of Industrial Processes Ship motion Control at Supervisory leve Tristan perez Doris saez, Aldo Cipriano and Andrzej w Ordos Hard Disk Drive Servo Systems(2nd Ed Ben M. Chen Tong H. lee, Kemao peng Robust Control of Diesel Ship propulsion and Venkatakrishnan Venkataramanan Nikolaos xiros Measurement, control, and Hydraulic servo-systems Communication Using IeeE 1588 Mohieddine jelali and andreas kroll John c. eidson Model-based Fault Diagnosis in dynamic Piezoelectric Transducers for vibration Systems Using ldentification Techniques Silvio simani. Cesare Fantuzzi and ron j Control and damping S O. Reza moheimani and andrew j Patton Fle eming Strategies for Feedback Linearisation Freddy Garces, Victor M. Becerra Manufacturing Systems Control design Chandrasekhar Kambhampati Stjepan Bogdan, Frank L. Lewis, Zdenko and Kevin warwick Kovacic and Jose mireles jr Robust autonomous guidance Windup in Controt Alberto isidori. Lorenzo marconi Peter hippe and Andrea serrani Nonlinear h,/ho Constrained feedback Dynamic Modelling of Gas Turbines Control Gennady G. Kulikov and Haydn A Murad Abu-Khalaf, Jie huang Thompson(Eds and frank l. lewis Control of Fuel cell Power Systems Practical Grey-box Process Identification Jay t Pukrushpan, Anna G. Stefanopoulou Torsten bohlin and huei peng Control of Traffic systems in buildings Fuzzy Logic, Identification and Predictive Sandor Markon, Hajime Kita, Hiroshi Kise Contro and Thomas bartz-Beielstein Jairo Espinosa, Joos Vandewalle andⅤ incent wertz Wind Turbine Control systems Fernando d. bianchi hernan de battista ptimal real-time Control of sewer and ricardo mantz Networks Magdalene marinaki and markos Advanced Fuzzy logic Technologies Papageorgiou in Industrial applications Ying bai, Hangi zhuang and dali wang Process Modelling for Control (Eds. Benoit codons Practical pld control Computational Intelligence in Time Series Antonio visioli Forecasting Ajoy K. Palit and Dobrivoje Popovic (continued after Index) Liuping Wang Model predictive Control system design and Implementation USing MAtlaB Springer Liuping Wang, PhD School of Electrical and Computer Engineering RMIT University Melbourne VIC 3000 australia ISBN978-1-84882-330-3 e-ISBN978-1-84882-331-0 DOI10.1007978-1-84882-331-0 Advances in Industrial Control IssN 1430-9491 A catalogue record for this book is available from the British Library Library of Congress Control Number: 2008940691 o 2009 Springer-Verlag London Limited MATLABC and Simulink@ are registered trademarks of The Math Works, Inc., 3 Apple Hill Drive, Natick, Maoi760-2098,Usa.http://www.mathworks.com 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 reprographic reproduction in accordance with the terms of licences ssued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers 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 Cover design: eStudio Calamar S L, Girona, Spain Printed on acid-free paper 987654321 springer. com advances in industrial Control Series editors Professor Michael J. Grimble, Professor of Industrial Systems and director Professor Michael A. Johnson, Professor(Emeritus)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 Gl IQE United Kingdom Series advisory board Professor e.f. camacho Escuela superior de ingenieros Universidad de sevilla Camino de los descubrimientos s/n 41092 Nevill Professor s. engell ehrstuhl fur Anlagensteuerungstechnik Fachbereich Chemietechnik Universitat dortmund 44221 Dortmund German y Professor g. goodwin Department of Electrical and Computer Engineerin The University of Newcastle aghan NSW2308 australia Professor t.. harris Department of Chemical Engineering Queens University Kingston, Ontario K7L 3N6 Canada Professor th. lee Department of Electrical and Computer Engineerin National University of Singapore 4 Engineering drive 3 Singapore 117576 Professor(Emeritus)O P. Malik Department of Electrical and Computer Engineerin University of Calgary 2500, University drive, NW Calgary, Alberta T2N 1N4 Canada Professor K-F Man Electronic Engineering Department City University of Hong Kong Tat chee avenue Kowloon Hong Kong Professor g. olsson Department of Industrial Electrical Engineering and Automation Lund Institute of Technology Box 118 221 00 Lund Swede Professor a. ray Department of Mechanical Engineering Pennsylvania state University 0329 Reber building University Park PA16802 USA Professor D.E. Seborg Chemical Engineering 3335 Engineering li University of California Santa barbara Barb CA93106 USA Doctor KK. tan Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117576 Professor l. y amamoto Department of Mechanical Systems and Environmental Engineering The University of Kitakyushu Faculty of Environmental Engineering 1-1, Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka, 808-0135 apan In memory of my parents 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 mo. Today s control software and technology offers the potential to implement more advanced control algorithms but often the preferred strategy of many industrial engineers is to design a robust and transparent process control structure that uses simple controllers This is one reason why the PId controller remains industry's most widely implemented controller despite the extensive developments of control theory however, this approach of structured control can create limitations on good process performance. One such limitation is the possible lack of a coordinator within the hierarchy that systematically achieves performance objectives. Another is the omission of a facility to accommodate and handle process operational constraints easily. The method of model predictive contro (MPC) can be used in different levels of the process control structure and is also able to handle a wide variety of process control constraints systematically. These are two of the reasons why MPC is often cited as one of the more popular advanced techniques for industrial process applications Surprisingly, MPC and the associated receding horizon control principle have a history of development and applications going back to the late 1960s; Jacques Richalet developed his predictive functional control technique for industrial application from that time onward. Work on using the receding horizon control concept with state-Space models can be identified in the literature of the 1970s, and the 1980s saw the emergence first of dynamic matrix control and then towards the end of the decade, of the influential generalised predictive control technique This field continues to develop and the Advances in Industrial Control monograph series has several volumes on the subject. These include Applied Series editors'foreword Predictive Control by S. Huang, K.K. Tan and T H Lee (isbn 978-1-85233-338 6, 2002), Fuzzy Logic, Identification and Predictive Control by J.J. Espinosa J. P L. Vandewalle and v. wertz (isbn 978-1-85233-828-2, 2005)and advanced Control of Industrial Processes by P. Tatjewski (IsBn 978-1-84628-634-6, 2007) In our related series, Advanced Textbooks in Control and Signal Processing, we have published Model Predictive Control by E.F. Camacho and C. Bordons(2nd edition, IsBn 978-1-85233-694-3, 2004), and Receding Horizon Control (ISBN 978-1-84628-024-5,2005)byWH. Kwon and s.Han To the above group of books we are now able to add this monograph, Model Predictive Control System Design and Implementation Using MATLaB, by Liuping wang. Professor Wang aims to provide both the industrial and the academic reader with a direct but graded route into understanding mpc as used in the solution of industrial control problems. The interleaved exposition, and MATLAB tutorials, allow the reader to work through a structured introduction to the design and implementation of MPC and use some related tools to condition tune and test the control design solutions Some features of mpc that makes it worthy of study as an industrial control technique include the technique uses simple concepts the controller tuning can be packaged for ease of use the technique can be used in either supervisory or primary control modes; and constraint handling is naturally accommodated by the method, and can be packaged for automated systematic constraint setup Professor Wangs book illustrates these issues and uses a small set of theoretical tools to great effect; these tools include the exponential weighting of signals, weights to achieve a prescribed degree of stability, re-parameterisation of the feedback using orthogonality principles, Laguerre and Kautz basis functions and quadratic programming. The book is structured so that discrete methods are considered first, and these are followed by continuous-time system techniques O the course of the book the matlab interludes result in readers constructing their own libraries of MPC routines that can be used in other control problems. Towards the end of the book, Professor Wang demonstrates the use of the mPC algorithms in some application studies. These range from a motor control application to the control of a food extruder process and these studies illustrate both the software and hardware aspects of the solutions The book's"hands-on"approach is expected to appeal to a wide readership ranging from the industrial control engineer to the postgraduate student in the process and control disciplines. Both will undoubtedly find the MATLaB demonstrations of the control concepts an invaluable tutorial route to understanding mpc in practice Industrial Control centre M. Grimble Glasgow M.A. Johnson Scotland UK 2008 【实例截图】
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