DocumentCode
2380930
Title
A fuzzy clustering method for the identification of fuzzy models for dynamic systems
Author
Zhao, J. ; Wertz, V. ; Gorez, R.
Author_Institution
Centre for Syst. Eng. & Appl. Mech., Univ. Catholique de Louvain, Belgium
fYear
1994
fDate
16-18 Aug 1994
Firstpage
172
Lastpage
177
Abstract
Fuzzy modeling is an important topic in fuzzy sets theory and applications. One particular fuzzy model structure, which can be used effectively to describe the behaviour of complex nonlinear systems, has been given by Takagi and Sugeno (1985). By means of a fuzzy clustering method, a new approach to the identification of this kind of fuzzy model is proposed, which integrates the structure and parameter identification steps, and/or the premise and consequence identification
Keywords
fuzzy logic; fuzzy set theory; large-scale systems; nonlinear control systems; parameter estimation; complex nonlinear systems; dynamic systems; fuzzy clustering method; fuzzy models; fuzzy sets theory; identification; parameter identification; Clustering methods; Fuzzy control; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Linear systems; Mathematical model; Nonlinear systems; Parameter estimation; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on
Conference_Location
Columbus, OH
ISSN
2158-9860
Print_ISBN
0-7803-1990-7
Type
conf
DOI
10.1109/ISIC.1994.367822
Filename
367822
Link To Document