Generating persistently exciting inputs for nonlinear dynamic system identification using fuzzy models

Author

Wan, Feng ; Wang, Li-Xin ; Zhu, He-Yun ; Sun, You-Xian

Author_Institution

Dept. of Electron. & Electr. Eng., Hong Kong Univ. of Sci. & Technol., China

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

505

Lastpage

508

Abstract

This article addresses parameter convergence problem in identification of nonlinear dynamic systems using fuzzy models. We first establish persistent excitation conditions and then propose several detailed algorithms to generate input signals that guarantee the convergence of the parameter estimates in the fuzzy system models to the true values in identifications of second-order nonlinear moving-average and auto-regressive-moving-average systems. Numerical example is given to illustrate the ideas and results

Keywords

autoregressive moving average processes; fuzzy logic; nonlinear dynamical systems; parameter estimation; autoregressive moving average systems; fuzzy models; nonlinear dynamic system identification; parameter convergence problem; persistently exciting inputs; second-order nonlinear moving average systems; Convergence; Electrical equipment industry; Fuzzy sets; Fuzzy systems; Nonlinear control systems; Nonlinear dynamical systems; Parameter estimation; Signal generators; Signal processing; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2001. The 10th IEEE International Conference on

Conference_Location

Melbourne, Vic.

Print_ISBN

0-7803-7293-X

Type

conf

DOI

10.1109/FUZZ.2001.1007359

Filename

1007359