Back-propagation neural network for nonlinear self-tuning adaptive control

Fu-Chuang Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

A backpropagation neural network is applied to a nonlinear self-tuning tracking problem. Traditional self-tuning adaptive control techniques can only deal with linear systems or some special nonlinear systems. The emerging backpropagation neural networks have the capability to learn arbitrary nonlinearity and show great potential for adaptive control applications. A scheme for combining backpropagation neural networks with self-tuning adaptive control techniques is proposed. The control mechanism is analyzed. Simulation results show that the new self-tuning scheme can deal with a large unknown nonlinearity.

Original languageEnglish
Title of host publicationProc IEEE Int Symp Intell Control 1989
EditorsArthur C. Sanderson, Alan A. Desrochers, Kimon Valavanis
PublisherPubl by IEEE
Pages274-279
Number of pages6
ISBN (Print)0818689870
DOIs
StatePublished - 1 Dec 1989
EventProceedings: IEEE International Symposium on Intelligent Control 1989 - Albany, NY, USA
Duration: 25 Sep 198926 Sep 1989

Publication series

NameProc IEEE Int Symp Intell Control 1989

Conference

ConferenceProceedings: IEEE International Symposium on Intelligent Control 1989
CityAlbany, NY, USA
Period25/09/8926/09/89

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