Adaptive NN consensus control for a class of nonlinear multi-agent time-delay systems
Wen G.-X.2; Philip Chen C.L.2
2013-12-01
Source PublicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Pages4941-4946
AbstractThis paper studies an adaptive neural consensus control for a class of nonlinear multi-agent time delay systems. The Radial Basis Function Neural Networks (RBFNN) are utilized to approximate the unknown nonlinear function of system dynamic. Based on Lyapunov analysis method, it is proven that the nonlinear multiagent system is stable and the consensus errors converge to a small neighborhood of zero. In contrast to the existing results, the advantage of the developed scheme is that the influence of time delay on the nonlinear multi-agent systems is eliminated. The effectiveness of the developed scheme is illustrated by a simulation example. © 2013 IEEE.
KeywordConsensus control Neural network Nonlinear multiagent systems State time delay
DOI10.1109/SMC.2013.844
URLView the original
Language英語
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.UMacau Research Institute
2.Universidade de Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wen G.-X.,Philip Chen C.L.. Adaptive NN consensus control for a class of nonlinear multi-agent time-delay systems[C],2013:4941-4946.
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