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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51564

Title: Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
Authors: Gwo-Ruey Yu
Chih-Yung Cheng
Yu-Chia Huang
Contributors: 國立臺灣海洋大學電機工程學系
Keywords: polynomial fuzzy control
Takagi–Sugeno fuzzy control
quantum-inspired evolutionary algorithms
Lyapunov function, sum of squares
Date: 2016-09
Issue Date: 2018-12-07T02:00:42Z
Publisher: International Journal of Systems Science
Abstract: Abstract: In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi–Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
Relation: 47(9) pp.2225-2236
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51564
Appears in Collections:[電機工程學系] 期刊論文

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