Title :
On the persistency of excitation in fuzzy systems
Author :
Chak, Chu Kwong ; Feng, Gang ; Cao, S.G.
Author_Institution :
Sch. of Electr. Eng., New South Wales Univ., Sydney, NSW, Australia
Abstract :
Fuzzy systems have been developed for more than two decades. Recently there appeared a number of results of fuzzy systems regarding the modelling and identification. Making use of the property that the consequence parameters are linear in fuzzy systems, recursive least squares algorithms are commonly adopted for training or adaptation of fuzzy systems. The condition for convergence of the parameters requires that the regressor vector are persistently exciting. This paper aims to show persistency of excitation in fuzzy systems
Keywords :
fuzzy control; fuzzy set theory; fuzzy systems; identification; least squares approximations; modelling; Takagi-Sugeno fuzzy systems; convergence; excitation persistency; fuzzy set theory; fuzzy systems; identification; modelling; recursive least squares; regressor vector; Control systems; Convergence; Fuzzy logic; Fuzzy sets; Fuzzy systems; Humans; Least squares methods; Neural networks; Takagi-Sugeno model; Vectors;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552286
