Fuzzy Logic, Identification and Predictive Control

by Jairo Jose Espinosa Oviedo, Joos P.L. Vandewalle, Vincent Wertz

Overview

Modern industrial processes and systems require adaptable advanced control prools able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose.

Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining.

This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.

Product Details

ISBN-13:	9781852338282
Publisher:	Springer London
Publication date:	10/14/2004
Series:	Advances in Industrial Control
Edition description:	2005
Pages:	264
Product dimensions:	6.10(w) x 9.25(h) x 0.24(d)

About the Author

Jairo Espinosa had a considerable experience of the practitioner side of advanced control systems and fuzzy systems in particular working with such companies as Zenith Data Systems in his native Colombia. There, he also won prizes for his academic work and for electronic design. He now works for IPCOS a company specialising in the design of advanced control systems for many process industries. This wil allow the author to draw on a good selection of industrial situations in writing the book.

Vincent Wertz is now head of the Automatic Control Group at Louvain where he is particularly active in Ph.D. supervision work (his contributions to the book will ensure relevance to the graduate market) and the book reflects all of his main research interests.

Table of Contents

Fuzzy Modeling.- Fuzzy Modeling.- Constructing Fuzzy Models from Input-Output Data.- Fuzzy Modeling with Linguistic Integrity: A Tool for Data Mining.- Nonlinear Identification Using Fuzzy Models.- Fuzzy Control.- Fuzzy Control.- Predictive Control Based on Fuzzy Models.- Robust Nonlinear Predictive Control Using Fuzzy Models.- Conclusions and Future Perspectives.

Editorial Reviews

From the reviews:

"New insights into the transfer of fuzzy methods into the modern control paradigms encompassing robust, model-based, PID-like, and predictive control are presented in this book. … Five appendices support the already extensive results of the chapters by proofs, explanations and illustrative examples. The book (263 pages, 138 figures, 95 references) is of interest to researchers in the field of data mining, artificial intelligence, modeling, and control. Also, the realistic examples provide good material to graduate students and engineers." (Ingmar Randvee, Zentralblatt MATH, Vol. 1061 (12), 2005)

From the Publisher