A Novel Identification Method for Generalized T-S Fuzzy Systems

被引：5
作者：
Huang, Ling [1 ]
Wang, Kai [1 ]
Shi, Peng [1 ,2 ,3 ]
Karimi, Hamid Reza [4 ]
机构：
[1] Harbin Univ Sci & Technol, Sch Automat, Harbin 150080, Peoples R China
[2] Univ Glamorgan, Dept Comp & Math Sci, Pontypridd CF37 1DL, M Glam, Wales
[3] Victoria Univ, Sch Sci & Engn, Melbourne, Vic 8001, Australia
[4] Univ Agder, Fac Sci & Engn, Dept Engn, N-4898 Grimstad, Norway
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2012年 / 2012卷
基金：
中国国家自然科学基金;
关键词：
ANT COLONY OPTIMIZATION; STABILIZATION CONDITIONS; ALGORITHM; DESIGN;
D O I：
10.1155/2012/893807
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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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页数：12
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