An adaptive learning control of uncertain robotic systems

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33 Scopus citations

Abstract

A novel iterative learning control scheme for precise tracking and parameter estimation of uncertain robotic systems is presented. The learning control scheme is globally convergent in the presence of disturbances and parameter variations. Under the PE condition in the domain of iteration sequence, it is proved that the estimated system parameters converge to the desired ones. The parameter estimator of the proposed learning control scheme does not use any system acceleration and inversion of the estimated inertia matrix, which makes the controller implementation more practical.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherPubl by IEEE
Pages1206-1211
Number of pages6
ISBN (Print)0780304500
StatePublished - 1991
EventProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3) - Brighton, Engl
Duration: 11 Dec 199113 Dec 1991

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2
ISSN (Print)0191-2216

Conference

ConferenceProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3)
CityBrighton, Engl
Period11/12/9113/12/91

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