Decentralized finite-time adaptive consensus of multiagent systems with fixed and switching network topologies

dc.contributor.authorTu, Zhizhong
dc.contributor.authorYu, Hui
dc.contributor.authorXia, Xiaohua
dc.contributor.emailxxia@up.ac.zaen_ZA
dc.date.accessioned2018-01-17T10:05:41Z
dc.date.available2018-01-17T10:05:41Z
dc.date.issued2017-01
dc.description.abstractIn this paper, finite-time adaptive consensus problem is investigated for first-order multiagent systems with unknown nonlinear dynamics. Linearly parameterized method is introduced to model unknown nonlinear dynamics of the systems. By only utilizing the local relative position state information between each agent and its neighbors, decentralized finite-time adaptive consensus algorithms are presented with directed fixed and switching network topologies which satisfy detailed balance condition. Based on classical Lyapunov analysis techniques, both finite-time stability and finite-time parameter convergence are guaranteed by making use of the proposed control algorithms. Finally, the results in Simulations part are presented to validate our main results.en_ZA
dc.description.departmentElectrical, Electronic and Computer Engineeringen_ZA
dc.description.librarianhj2018en_ZA
dc.description.sponsorshipThis work is supported in part by National Natural Science Foundation (NNSF) of China (61273183, 61174216, 61374028 and 61304162).en_ZA
dc.description.urihttp://www.elsevier.com/locate/neucomen_ZA
dc.identifier.citationTu, Z.Z., Yu, H. & Xia, X.H. 2017, 'Decentralized finite-time adaptive consensus of multiagent systems with fixed and switching network topologies', Neurocomputing, vol. 219, pp. 59-67.en_ZA
dc.identifier.issn0925-2312 (print)
dc.identifier.issn1872-8286 (online)
dc.identifier.other10.1016/j.neucom.2016.09.013
dc.identifier.urihttp://hdl.handle.net/2263/63584
dc.language.isoenen_ZA
dc.publisherElsevieren_ZA
dc.rights© 2016 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. 219, pp. 59-67, 2017. doi : 10.1016/j.neucom.2016.09.013.en_ZA
dc.subjectMultiagent systemen_ZA
dc.subjectUnknown nonlinear dynamicsen_ZA
dc.subjectFinite-time consensusen_ZA
dc.subjectFinite-time parameter convergenceen_ZA
dc.titleDecentralized finite-time adaptive consensus of multiagent systems with fixed and switching network topologiesen_ZA
dc.typePostprint Articleen_ZA

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