A Novel Identification Method for Generalized T-S Fuzzy Systems
Joint Authors
Huang, Ling
Wang, Kai
Shi, Peng
Karimi, Hamid Reza
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-21
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Huang, Ling& Wang, Kai& Shi, Peng& Karimi, Hamid Reza. 2012. A Novel Identification Method for Generalized T-S Fuzzy Systems. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1002056
Modern Language Association (MLA)
Huang, Ling…[et al.]. A Novel Identification Method for Generalized T-S Fuzzy Systems. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1002056
American Medical Association (AMA)
Huang, Ling& Wang, Kai& Shi, Peng& Karimi, Hamid Reza. A Novel Identification Method for Generalized T-S Fuzzy Systems. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1002056
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1002056
