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
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;
Conference_Titel :
Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
0-7803-1990-7
DOI :
10.1109/ISIC.1994.367822
