Nonlinear Fixed-Time Bipartite Consensus Algorithm for Multiagent Systems

Sifan Yang, Pengfei Xing, Guobin Li, Jin Tao

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

Abstract

In the paper, we consider the uncertain nonlinear multi-agent systems over antagonistic networks and design an algorithm to achieve bipartite consensus in a fixed time. The algorithm drives each agent of multi-agent systems to achieve bipartite consensus, and the achieved bipartite consensus has the same modules but opposite signs when the antagonistic network is structurally balanced. Compared with the traditional asymptotic consensus and the finite-time consensus, the fixed-time bipartite consensus can reach convergence faster, and the settling time is independent of the initial states of the system. Finally, the simulation results verify the validity of the proposed theoretical results.
Original languageEnglish
Title of host publication2021 33rd Chinese Control and Decision Conference (CCDC)
PublisherIEEE
Pages4509-4513
Number of pages5
ISBN (Electronic)978-1-6654-4089-9
ISBN (Print)978-1-6654-3129-3
DOIs
Publication statusPublished - 30 Nov 2021
MoE publication typeA4 Conference publication
EventChinese Control and Decision Conference - Kunming, China
Duration: 22 May 202124 May 2021
Conference number: 33

Publication series

NameChinese control and decision conference
ISSN (Electronic)1948-9447

Conference

ConferenceChinese Control and Decision Conference
Abbreviated title CCDC
Country/TerritoryChina
CityKunming
Period22/05/202124/05/2021

Keywords

  • Protocols
  • Simulation
  • Delay effects
  • Consensus algorithm
  • Control systems
  • Multi-agent systems
  • Convergence

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