Overview

In the classic example of a steam engine governor an increase in speed immediately results in a decrease in steam supplied, so slowing the engine. In many instances there is a considerable lag between the corrective action (decrease in steam) and resumption of the correct state. For example, the output of a base chemical plant may take minutes or even hours to respond to pressure of temperature changes imposed on the plant. In these cases predictive control is required. Without a detailed running history of the chemical plant (in this example) it is then necessary to use model-based predictive control (rather than experience based predictive control). This book is devoted to all aspects of Model-Based Predictive Control, including new developments in the theory of the subect and current applications of MBPC to real processes. Topics included are: algorithm developments, industrial applications, and comparison with other approaches.

Full Product Details

Author:   David Clarke (Professor of Control Engineering, Department of Engineering Science, Professor of Control Engineering, Department of Engineering Science, University of Oxford)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Dimensions:   Width: 19.60cm , Height: 3.60cm , Length: 25.10cm
Weight:   1.184kg
ISBN:  

9780198562924

ISBN 10:   0198562926
Pages:   548
Publication Date:   05 May 1994
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   To order  
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

Table of Contents

D.W. Clarke: Advances in model-based predictive control J. Richalet, C. de Prada, & M. Sanzo: Matching the uncertainty of the model given by global identification techniques to the robustness of a model-based predictive controller G. de Nicolaom & R. Scattolini: Stability and output terminal constraints in predictive control K.M. Hangos, Zs. Csaki, & E.I. Varga: Use of qualitative models for the choice of design parameters of model-based predictive controllers G. Montague, & M.J. Willis: Artificial neural network model-based control Y. Tan, & R. de Keyser: Neural network based adaptive predictive control D. Matko: Fuzzy generalized predictive controller S. Lall, & K. Glover: A game theoretic approach to moving horizon control M. Karny, & A. Halouskova: Pre-tuning of self-tuners L. Chisei, & E. Mosca: Stabilizing predictive control: the singular transition-matrix case T.-W. Yoon: Robust adaptive predictive control H. Demircioglu: Continuous-time generalised predictive control (CGPC): Implementation issues A. Ordys: Evaluation of stochastic characteristics for a constrained GPC algorithm M.B. Zarrop, & J.J. Troyas: Model-based predictive control for two-dimensional dynamic processes K. Dadd, & P. Krauss: Model-based predictive controller with Kalman filtering for state estimation J. Taylor, P.C. Young, & A. Chotai: On the relationship between GPC and PIP controllers C. de Prada, & J. Serrano: A comparative study of GPC and DMC controllers A.P. de Madrid, M. Santos, S. Dormido, & F. Morilla: Constrained generalized predictive control with dynamic programming J.C. Allwright: Min-max model-based predictive control M. Morari: Stability and robustness of constrained model predictive control M. Alamir, & G. Bornard: New sufficient conditions for global stability of receding horizon control for discrete-time nonlinear systems L. Kershenbaum, D.Q. Mayne, R. Pytlak, & R.B. Vinter: Nonlinear model-based predictive control S. Sommer: Model-based predictive control methods based on non-linear and bilinear parametric system descriptions V. Balakrishnan, Z.Q. Zheng, & M. Morari: Stability results for constrained model predictive control P.O. Scokaert: Stability in constrained predictive control S.A. Heise, & J.M. Maciejowski: Stability of constrained MBPC using an internal model control structure C.M. Chow: Actuator nonlinearities in predictive control J.A. Rossiter, & B. Kouvaritakis: Advances in constrained generalized predictive control with application to a dynamometer model A.G. Kuznetsov: Application of constrained GPC for improving performance of controlled plants D.A. Linkens, & M. Mahfouf: Generalised predictive control in clinical anaesthesia E.P. Evans, & R. Harpin: Modelling control in a large water treatment works F. Berlin, & P.M. Frank: Design and realization of a MIMO predictive controller for a 3-tank system K. Warwick, & E. Kassapakis: Predictive control for target tracking D. Dumur, & P. Boucher: Predictive control application in the machine-tool field E. Camacho: Application of GPC to a solar power plant

Reviews

`The book will be of interest to both researchers and designers, and control engineers.' Aslib Book Guide, Vol.59, no. 11, Nov 1994

The book will be of interest to both researchers and designers, and control engineers. Aslib Book Guide, Vol.59, no. 11, Nov 1994

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