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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40403

Title: Intelligent Fuzzy Control with Imperfect Premise Matching Concept for Complex Nonlinear Multiplicative Noised Systems
Authors: Wen-Jer Chang;Che-Pin Kuo;Cheung-Chieh Ku
Contributors: 國立臺灣海洋大學:輪機工程學系
Keywords: Nonlinear system with multiplicative noise;Takagi–Sugeno fuzzy model;Imperfect premise matching;Linear matrix inequality
Date: 2015-04-22
Issue Date: 2017-01-18T06:39:52Z
Publisher: Neurocomputing
Abstract: Abstract
This paper provides the criterion for discussing stability analysis and synthesis of a class of complex nonlinear systems represented by Takagi–Sugeno fuzzy models with multiplicative noise. In the consequent part of the T–S fuzzy models, the Itô’s stochastic differential equations are introduced to represent the linear subsystems with multiplicative noise. Under the concept of imperfect premise matching, a novel fuzzy controller is designed without limitation of sharing the same membership function of fuzzy models. In other words, the imperfect premise matching technique provides a more general approach in designing fuzzy controllers. The advantage of the proposed fuzzy controller design method is that it can be enhanced more flexibility and robustness than well-known parallel distributed compensation based fuzzy control approach. At last, two numerical examples are given to illustrate the usefulness and effectiveness of proposed fuzzy controller design method.
Relation: 154, pp.276-283
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40403
Appears in Collections:[輪機工程學系] 期刊論文

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