Fuzzy Logic, Identification and Predictive Control
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Beschreibung
The complexity and sensitivity of modern industrial processes and systems increasingly require adaptable advanced control protocols. These controllers have to be able to deal with circumstances demanding "judgement" rather than simple "yes/no", "on/off" responses, circumstances where an imprecise 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 in this form of expert control system.
Divided into two parts, 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-world industrial systems and simulations. The second part demonstrates the exploitation of such models to design control systems employing techniques like data mining.
Fuzzy Logic, Identification and Predictive Control is a comprehensive introduction to the use of fuzzy methods in many different control paradigms encompassing robust, model-based, PID-like and predictive control. This combination of fuzzy control theory and industrial serviceability 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.
Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Demand for this book will come from research engineers looking to find ways to deal with systems (especially non-linear systems) which have been difficult to deal with in traditional control and from industrial control engineers looking to take advantage of the low-solution costs associated with the implementation of fuzzy methods in improving existing control protocols.
For the first time in monograph form, the reader can learn the use of fuzzy models in predictive control The reader will learn a novel approach to the construction of fuzzy models which compounds the data from real situations with the consideration of linguistic integrity which is increasingly beneficial in dealing with the vagaries of real-life control Includes supplementary material: sn.pub/extras
Autor*in
Jairo Jose Espinosa Oviedo
Themen in »Fuzzy Logic, Identification and Predictive Control«
Control Control Applications Data Mining Fuzzy Control Fuzzy Modelling Intelligent Control Nonlinear Predictive Control control engineering modeling simulation complexity
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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)
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