Approximating nonlinear systems by nonlinear ARMA and AR models

Author

DeGroat, Ronald D. ; Hunt, Louis R. ; Linebarger, Darel A.

Author_Institution

Center for Eng. Math., Texas Univ., Richardson, TX, USA

Volume

5

fYear

1992

fDate

23-26 Mar 1992

Firstpage

465

Abstract

A nonlinear autoregressive (AR) and AR moving average (ARMA) approximation theory is developed for an important class of nonlinear systems, namely, feedback linearizable systems with polynomial nonlinearities. The focus is on nonlinear AR models (NAR) because (1) the NAR parameters can be estimated via linear equations, (2) NAR models can be used to approximate almost any nonlinear system, and (3) compact difference equation and state space forms exist for this class of models

Keywords

approximation theory; difference equations; nonlinear systems; parameter estimation; polynomials; signal processing; approximation theory; autoregressive models; autoregressive moving average models; compact difference equation; feedback linearizable systems; linear equations; nonlinear systems; parameter estimation; polynomial nonlinearities; signal processing; state space forms; Difference equations; Ear; Feedback; Linear systems; Mathematical model; Nonlinear control systems; Nonlinear systems; Polynomials; Signal processing; State-space methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226582

Filename

226582