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Get Free AccessIn 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.
Ling Huang, Kai Wang, Peng Shi, Hamid Reza Karimi (2012). A Novel Identification Method for Generalized T‐S Fuzzy Systems. Mathematical Problems in Engineering, 2012(1), DOI: 10.1155/2012/893807.
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Type
Article
Year
2012
Authors
4
Datasets
0
Total Files
0
Language
English
Journal
Mathematical Problems in Engineering
DOI
10.1155/2012/893807
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