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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40360

Title: LMI-based Fuzzy Controller Design with Minimum Upper Bound Input Energy and State Variance Constraints for Discrete Fuzzy Stochastic Systems
Authors: W. J. Chang;C. C. Shing
Contributors: 國立臺灣海洋大學:輪機工程學系
Date: 2004-01
Issue Date: 2017-01-17T08:18:01Z
Publisher: Journal of Intelligent and Fuzzy Systems
Abstract: Abstract:In this paper, a fuzzy controller design problem is considered for the discrete-time Takagi-Sugeno (T-S) fuzzy stochastic systems. The main purpose of this paper is to provide a systematic fuzzy controller design procedure for the discrete-time nonlinear stochastic systems, which are modeled by the T-S type fuzzy systems. A methodology is developed to find the discrete-time fuzzy controllers for minimizing upper bound control input energy and achieving state variance constraints for discrete-time T-S fuzzy stochastic systems. It is shown that the present approach can be used to solve the linear feedback control gains for each rule of the T-S fuzzy controllers using the Linear Matrix Inequality (LMI) technique. Finally, we apply the proposed controller design method to control a truck-trailer system to show the utility of the present approach.
Relation: 15(2), pp.115-124
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40360
Appears in Collections:[輪機工程學系] 期刊論文

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