A Novel Identification Method for Generalized T-S Fuzzy Systems

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Huang, Ling, Wang, Kai, Shi, Peng and Karimi, Hamid Reza (2012) A Novel Identification Method for Generalized T-S Fuzzy Systems. Mathematical Problems in Engineering, 2012. ISSN 1024-123X

Abstract

In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/23372
DOI 10.1155/2012/893807
Official URL http://www.hindawi.com/journals/mpe/2012/893807/
Subjects Historical > FOR Classification > 0103 Numerical and Computational Mathematics
Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Keywords ResPubID25583, nonlinear systems, fuzzy systems, colony algorithm, genetic algorithm, proposed algorithm
Citations in Scopus 4 - View on Scopus
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