Leader-following consensus protocol for second-order multi-agent systems using neural networks

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Abstract

In this paper, an adaptive leader-following consensus protocol is proposed for second-order multi-agent systems with unknown nonlinear dynamics based on neural networks (NNs), and it is proved that if at least one agent in each connected component of the fixed interaction graph is connected to the leader, all agents can asymptotically track the leader. By estimating the tracking error in terms of L2 norm, the transient performance of multi-agent systems can be significantly improved. Finally, a numerical example is included to the proposed protocol.

Original languageEnglish
Title of host publicationProceedings of the 27th Chinese Control Conference, CCC
Pages535-539
Number of pages5
DOIs
StatePublished - 2008
Event27th Chinese Control Conference, CCC - Kunming, Yunnan, China
Duration: 16 Jul 200818 Jul 2008

Publication series

NameProceedings of the 27th Chinese Control Conference, CCC

Conference

Conference27th Chinese Control Conference, CCC
Country/TerritoryChina
CityKunming, Yunnan
Period16/07/0818/07/08

Keywords

  • Leader-following consensus protocol
  • Multi-agent systems
  • Neural networks
  • Nonlinear dynamics

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