A constructive approach for nonlinear system identification using multilayer perceptrons

Author

Choi, Ju-Yeop ; Van Landingham, H.F. ; Bingulac, Stanoje

Author_Institution

Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

Volume

26

Issue

2

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

307

Lastpage

312

Abstract

This paper combines a conventional method of multivariable system identification with a dynamic multi-layer perceptron (MLP) to achieve a constructive method of nonlinear system identification. The class of nonlinear systems is assumed to operate nominally around an equilibrium point in the neighborhood of which a linearized model exists to represent the system, although normal operation is not limited to the linear region. The result is an accurate discrete-time nonlinear model, extended from a MIMO linear model, which captures the nonlinear behavior of the system

Keywords

genetic algorithms; multilayer perceptrons; multivariable control systems; neural nets; nonlinear systems; parameter estimation; constructive approach; discrete-time nonlinear model; equilibrium point; linearized model; multilayer perceptrons; multivariable system identification; nonlinear system identification; Control systems; Linear systems; MIMO; Multilayer perceptrons; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Resists; Working environment noise;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/3477.485881

Filename

485881