Neuro-adaptive consensus tracking of multiagent systems with a high-dimensional leader and directed switching topologies

Guanghui Wen, Peijun Wang, Yuezu Lv

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

Abstract

This brief addresses the practical consensus tracking problem for multiagent systems (MASs) with a high-dimensional leader and uncertain dynamics over directed switching topologies based on the neuro-adaptive approach. First, an observer is embedded in each follower to estimate the leader's state. And it is proven that the observer will track the leader asymptotically if the average dwell time (ADT) is sufficiently large. Furthermore, a discontinuous feedback controller plus a compensation controller is designed for each follower such that the error between the followers' states and their associated observers' states will converge into a bounded set. It is worth noting that the obtained residual error depends neither on the neural network (NN) approximation error nor on the external disturbances. Finally, a simulation is performed to validate the obtained theoretical result.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Pages5966-5971
Number of pages6
ISBN (Electronic)9789881563972
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
Volume2019-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference38th Chinese Control Conference, CCC 2019
Country/TerritoryChina
CityGuangzhou
Period27/07/1930/07/19

Keywords

  • Consensus tracking
  • Directed switching topologies
  • High-dimensional leader
  • Multiagent systems
  • Neuro-adaptive

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