• DocumentCode
    3601235
  • Title

    Impulsive Multiconsensus of Second-Order Multiagent Networks Using Sampled Position Data

  • Author

    Zhi-Hong Guan ; Guang-Song Han ; Juan Li ; Ding-Xin He ; Gang Feng

  • Author_Institution
    Coll. of Autom., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • Volume
    26
  • Issue
    11
  • fYear
    2015
  • Firstpage
    2678
  • Lastpage
    2688
  • Abstract
    A multiconsensus problem of multiagent networks is solved in this paper, where multiconsensus refers to that the states of multiple agents in each subnetwork asymptotically converge to an individual consistent value when there exist information exchanges among subnetworks. A distributed impulsive protocol is proposed to achieve multiconsensus of second-order multiagent networks in terms of three categories: 1) stationary multiconsensus; 2) the first dynamic multiconsensus; and 3) the second dynamic multiconsensus. This impulsive protocol utilizes only sampled position data and is implemented at sampling instants. For those three categories of multiconsensus, the control parameters in the impulsive protocol are designed, respectively. Moreover, necessary and sufficient conditions are derived, under which each multiconsensus can be reached asymptotically. Several simulations are finally provided to demonstrate the effectiveness of the obtained theoretical results.
  • Keywords
    distributed control; multi-agent systems; network theory (graphs); sampled data systems; distributed impulsive protocol; first dynamic multiconsensus; impulsive multiconsensus problem; necessary conditions; sampled position data; sampling instants; second dynamic multiconsensus; second-order multiagent networks; stationary multiconsensus; sufficient conditions; Asymptotic stability; Educational institutions; Eigenvalues and eigenfunctions; Equations; Multi-agent systems; Protocols; Vehicle dynamics; Dynamic multiconsensus; impulsive protocol; multiagent networks; stationary multiconsensus; stationary multiconsensus.;
  • fLanguage
    English
  • Journal_Title
    Neural Networks and Learning Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2162-237X
  • Type

    jour

  • DOI
    10.1109/TNNLS.2015.2389531
  • Filename
    7021948