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Fuzzy Modeling for Control

Name: Fuzzy Modeling for Control
Author: Robert Babuska
ISBN: 9789401060400

by Robert Babuska

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Overview

Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering point of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements fuzzy identification, and on the design of nonlinear controllers based on fuzzy models. The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.

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Booknews

Babuska's (control engineering, Delft U. of Technology, the Netherlands) strategy is to develop transparent rule-based fuzzy models that can accurately predict the quantities of interest and at the same time provide insight into the system that generated the data. He highlights the selection of appropriate model structures in terms of the dynamic properties, as well as the internal structure of the fuzzy rules<-->linguistic, relational, or Takagi-Sugeno type. His methodology employees fuzzy clustering techniques to partition the available data into subsets characterized by linear behavior, then exploits the relationships between the presented identification method and linear regression to combine fuzzy logic techniques with standard tools for identifying systems. Annotation c. by Book News, Inc., Portland, Or.