Neuro-adaptive tracking control algorithms for a class of nonlinear systems

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Abstract

Presents a neural network (NN) based adaptive control method for a class of nonlinear dynamic systems. Two NN units are incorporated into control scheme which are shown to be effective in attenuating NN reconstruction error and other lumped system uncertainties. Since the control scheme is based upon the worst case that the NNs might behave, it exhibits a "fail-safe" feature, which enhances the reliability of the NN-based control scheme. Stable online weights tuning algorithms are derived based on Lyapunov stability theory. The control method is extended to robotic systems.
Original languageEnglish
Title of host publicationProceedings of the 1997 American Control Conference
Pages664-668
Number of pages5
Volume1
DOIs
Publication statusPublished - 1997
Externally publishedYes
Event1997 American Control Conference - Albuquerque, United States
Duration: 4 Jun 19976 Jun 1997

Publication series

NameProceedings of the American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume1
ISSN (Print)0743-1619

Conference

Conference1997 American Control Conference
Country/TerritoryUnited States
CityAlbuquerque
Period4/06/976/06/97

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