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Type: Journal article
Title: A novel identification method for generalized T-S fuzzy systems
Author: Huang, L.
Wang, K.
Shi, P.
Karimi, H.
Citation: Mathematical Problems in Engineering, 2012; 2012:1-12
Publisher: Gordon Breach Sci Publ Ltd
Issue Date: 2012
ISSN: 1024-123X
Statement of
Ling Huang, Kai Wang, Peng Shi and Hamid Reza Karimi
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.
Description: Extent: 12p.
Rights: Copyright © 2012 Ling Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1155/2012/893807
Appears in Collections:Aurora harvest 4
Electrical and Electronic Engineering publications

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