Asymptotic consensus tracking of uncertain multi-agent systems with a high-dimensional leader: A neuro-adaptive approach

  • Peijun Wang
  • , Xinghuo Yu
  • , Wenwu Yu
  • , Guanghui Wen
  • , Jinhu Lü

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this note, the asymptotic consensus tracking problem is addressed for uncertain multi-agent systems (MASs) with undirected communication topologies and a high-dimensional leader, where the uncertainties may contain unmodeled dynamics and external disturbance which are prior unknown. To remove the effect of high-dimensional leader, an observer based compensation controller is firstly designed. A neural-adaptive based feedback controller is then designed. Note that the feedback term contains a discontinuous controller which is used to eliminate the effect of imprecise approximation of neural network. Furthermore, if the leader is assumed to be globally reachable, it is shown that asymptotic consensus tracking is achieved in MAS by choosing appropriate control parameters. The obtained theoretical result is finally validated by simulation.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6162-6166
Number of pages5
ISBN (Electronic)9781509066841
DOIs
StatePublished - 26 Dec 2018
Event44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States
Duration: 20 Oct 201823 Oct 2018

Publication series

NameProceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Country/TerritoryUnited States
CityWashington
Period20/10/1823/10/18

Keywords

  • Asymptotic consensus tracking
  • High-dimensional leader
  • Multiagent system
  • Neuro-adaptive

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