An IV-QR Algorithm for Neuro-Fuzzy Multivariable Online Identification

Author

Serra, Ginalber ; Bottura, Celso

Author_Institution

Dept. of Machines, Components & Intelligent Syst., State Univ. of Campinas

Volume

15

Issue

2

fYear

2007

fDate

4/1/2007 12:00:00 AM

Firstpage

200

Lastpage

210

Abstract

In this paper, a new algorithm for neuro-fuzzy identification of multivariable discrete-time nonlinear dynamic systems, more specifically applied to consequent parameters estimation of the neuro-fuzzy inference system, is proposed based on a decomposed form as a set of coupled multiple input and single output (MISO) Takagi-Sugeno (TS) neuro-fuzzy networks. An on-line scheme is formulated for modeling a nonlinear autoregressive with exogenous input (NARX) recurrent neuro-fuzzy structure from input-output samples of a multivariable nonlinear dynamic system in a noisy environment. The adaptive weighted instrumental variable (WIV) algorithm by QR factorization based on the numerically robust orthogonal Householder transformation is developed to modify the consequent parameters of the TS multivariable neuro-fuzzy network

Keywords

autoregressive processes; discrete time systems; fuzzy neural nets; fuzzy reasoning; multivariable control systems; neurocontrollers; nonlinear control systems; parameter estimation; recurrent neural nets; IV-QR algorithm; QR factorization; TS multivariable neuro-fuzzy network; Takagi-Sugeno neuro-fuzzy networks; adaptive weighted instrumental variable algorithm; coupled multiple input single output neuro-fuzzy network; exogenous input structure; multivariable discrete-time nonlinear dynamic systems; neuro-fuzzy inference system; neuro-fuzzy multivariable online identification; nonlinear autoregressive structure; orthogonal Householder transformation; parameter estimation; recurrent neuro-fuzzy structure; Fuzzy neural networks; Fuzzy systems; Inference algorithms; Instruments; Noise cancellation; Nonlinear dynamical systems; Predictive models; Robustness; Takagi-Sugeno model; Working environment noise; Fuzzy systems; instrumental variable; multivariable identification; neural networks;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/TFUZZ.2006.879997

Filename

4142762