Nonlinear System Modeling using Neural Networks

Abstract

Artificial neural networks have gained increasing popularity in control area in recent years. This paper outlines the application of a neural network based identification approach to a dynamical nonlinear system, a cantilever plate with distributed actuators and sensors. The type of neural networks utilized are multi-layer perceptrons with the backpropagation (BP) learning method. The identifier is implemented in discrete-time domain, and its performance is compared with a linear model from a previous result, that used frequency domain method. The time-domain neural network approach displays better nonlinear dynamical properties. A new efficient scheme to train the BP neural networks with a large amount of data is also introduced.

Department(s)

Electrical and Computer Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 The Authors, All rights reserved.

Publication Date

01 Dec 1997

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