Title :
Identification of fuzzy T-S ARMAX models
Author :
Lee, Bore-kuen ; Chen, Bor-Sen
Author_Institution :
Dept. of Electr. Eng., Chung Hua Univ., Hsinchu, Taiwan
Abstract :
Identification of a T-S fuzzy ARMAX model is addressed in this paper. From the fuzzy ARMAX model, a fuzzy one-step ahead prediction model is developed. A recursive least square algorithm is then proposed to identify the parameters in the consequent part of a T-S fuzzy ARMAX system. Properties of the parameter estimates are rigorously derived. This work is an extension of the results of identification of stochastic linear systems.
Keywords :
autoregressive moving average processes; fuzzy set theory; fuzzy systems; least squares approximations; linear systems; recursive estimation; stochastic systems; T-S fuzzy ARMAX model; fuzzy one step ahead prediction model; fuzzy system; parameter estimation; parameter identification; recursive least square algorithm; stochastic linear systems; Fuzzy sets; Fuzzy systems; Least squares methods; Linear systems; Polynomials; Power system modeling; Predictive models; Stochastic processes; Stochastic resonance; Stochastic systems;
Conference_Titel :
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8353-2
DOI :
10.1109/FUZZY.2004.1375548
