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A Novel Identification Method for Generalized T-S Fuzzy Systems

Huang, Ling and Wang, Kai and 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

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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.

Item Type: Article
Uncontrolled Keywords: ResPubID25583, nonlinear systems, fuzzy systems, colony algorithm, genetic algorithm, proposed algorithm
Subjects: FOR Classification > 0103 Numerical and Computational Mathematics
Faculty/School/Research Centre/Department > School of Engineering and Science
Depositing User: Yimin Zeng
Date Deposited: 02 Feb 2014 03:23
Last Modified: 10 Mar 2015 03:30
URI: http://vuir.vu.edu.au/id/eprint/23372
DOI: 10.1155/2012/893807
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