A Novel Identification Method for Generalized T-S Fuzzy Systems

Ling Huang, Kai Wang, Peng Shi and Hamid Reza Karimi

Mathematical Problems in Engineering, 2012, vol. 2012, 1-12

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.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:893807

DOI: 10.1155/2012/893807

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