Adaptive leaderless consensus of agents in jointly connected networks

Show simple item record Yu, Hui Xia, Xiaohua 2017-05-12T09:56:42Z 2017-06
dc.description.abstract In this paper, the leaderless consensus problem of multi-agent systems with jointly connected topologies and nonlinear dynamics is considered, in which the nonlinear dynamics are assumed to be non-identical and unknown. The unknown nonlinear dynamics existing in the systems are assumed to be linearly parameterized, and an adaptive design method for leaderless multiagent systems is presented. By just using the relative position information between each agent and its neighbours, a distributed adaptive consensus control algorithm for the considered systems is proposed, in which the network graphs are jointly connected. Both the global uniform asymptotical stability and the global uniform asymptotical parameter convergence analysis of the adaptive control algorithm are carried out by using adaptive control theory, Lyapunov theory and algebraic graph theory. Finally, an example is given to illustrate the validity of our theoretical results. en_ZA
dc.description.department Electrical, Electronic and Computer Engineering en_ZA
dc.description.embargo 2018-06-30
dc.description.librarian hb2017 en_ZA
dc.description.sponsorship The National Natural Science Foundation (NNSF) of China (61273183, 61374028 and 61304162). en_ZA
dc.description.uri en_ZA
dc.identifier.citation Yu, H & Xia, XH 2017, 'Adaptive leaderless consensus of agents in jointly connected networks', Neurocomputing, vol. 241, pp. 64-70. en_ZA
dc.identifier.issn 0925-2312 (print)
dc.identifier.issn 1872-8286 (online)
dc.identifier.other 10.1016/j.neucom.2017.02.031
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2017 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Neurocomputing, vol. 241, pp. 64-70, 2017. doi : 10.1016/j.neucom.2017.02.031. en_ZA
dc.subject Adaptive consensus en_ZA
dc.subject Decentralized control en_ZA
dc.subject Parameter convergence en_ZA
dc.subject Jointly connected topology en_ZA
dc.subject Multi-agent system en_ZA
dc.title Adaptive leaderless consensus of agents in jointly connected networks en_ZA
dc.type Postprint Article en_ZA

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