Identification of nonlinear dynamic systems using functional link artificial neural networks

Author

Patra, Jagdish C. ; Pal, Ranendra N. ; Chatterji, B.N. ; Panda, Ganapati

Author_Institution

Dept. of Appl. Electron. & Instrum. Eng., Regional Eng. Coll., Orissa, India

Volume

29

Issue

2

fYear

1999

fDate

4/1/1999 12:00:00 AM

Firstpage

254

Lastpage

262

Abstract

We have presented an alternate ANN structure called functional link ANN (FLANN) for nonlinear dynamic system identification using the popular backpropagation algorithm. In contrast to a feedforward ANN structure, i.e., a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which nonlinearity is introduced by enhancing the input pattern with nonlinear functional expansion. With proper choice of functional expansion in a FLANN, this network performs as good as and in some cases even better than the MLP structure for the problem of nonlinear system identification

Keywords

backpropagation; computational complexity; neural nets; nonlinear dynamical systems; parameter estimation; backpropagation algorithm; feedforward ANN structure; functional link ANN; functional link artificial neural networks; multilayer perceptron; nonlinear dynamic system identification; nonlinear dynamic systems identification; nonlinear system identification; nonlinearity; Artificial neural networks; Control systems; Function approximation; Multilayer perceptrons; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Signal processing algorithms; System identification; Vectors;

fLanguage

English

Journal_Title

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

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/3477.752797

Filename

752797