Advances in Fuzzy Control
By: edited by Dimiter Driankov, Rainer Palm
Contributors: Palm, Rainer
Series: Studies in Fuzziness and Soft Computing -- 16; Studies in Fuzziness and Soft Computing -- 16
Publisher: Physica-Verlag HD; Imprint: Physica
Published: 1998
Place of publication: Heidelberg
Language: eng
Format: [electronic resource] /
Number of pages: 421
ISBN-13: 9783662110539; 9783790818864
Subjects: Engineering; Computer science; Management information systems; Optical pattern recognition; Physics; Artificial intelligence
Description: Model-based fuzzy control uses a given conventional or a fuzzy open loop of the plant under control in order to derive the set of fuzzy if-then rules constituting the corresponding fuzzy controller. Furthermore, of central interest are the consequent stability, performance, and robustness analysis of the resulting closed loop system involving a conventional model and a fuzzy controller, or a fuzzy model and a fuzzy controller. The major objective of the model-based fuzzy control is to use the full available range of existing linear and nonlinear design of such fuzzy controllers which have better stability, performance, and robustness properties than the corresponding non-fuzzy controllers designed by the use of these same techniques.
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Table of contents: title: Stability Analysis of Fuzzy Models; title: Inverse Fuzzy Models; title: Adaptive Fuzzy Control; title: Predictive Fuzzy Control; title: Gain Scheduled Fuzzy Control.