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Mean Square Consensus of General Linear Multiagent Systems with Communication Noises under Switching Topologies

Author

Listed:
  • Kairui Chen
  • Chuance Yan
  • Qijun Ren
  • Xianxian Zeng
  • Junwei Wang

Abstract

This paper investigates the distributed consensus problem of general linear multiagent systems (MASs) with communication noises under fixed and Markovian switching topologies, respectively. Each agent can obtain full state of itself and receive its neighbors’ state with noises, where intensities of noises are vector functions of relative states of agents. Bearing in mind the above constrains, a consensus protocol is proposed, where the gain matrix is obtained by the algebraic Riccati equation and the coupling strength is restricted in a given interval. By using the stochastic stability theorem, we show that mean square consensus is achieved in fixed topology case and switching topologies case, respectively. Furthermore, an estimation of the exponential convergence rate of consensus is given explicitly. Finally, simulation examples are given to show the correctness of the proposed results.

Suggested Citation

  • Kairui Chen & Chuance Yan & Qijun Ren & Xianxian Zeng & Junwei Wang, 2022. "Mean Square Consensus of General Linear Multiagent Systems with Communication Noises under Switching Topologies," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:1337959
    DOI: 10.1155/2022/1337959
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    References listed on IDEAS

    as
    1. Xinxin Xie & Xiaowu Mu, 2020. "Output feedback containment control of multi-agent systems with semi-Markovian switching topologies and input-bounded leaders," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(16), pages 3299-3319, December.
    2. Li, Zheng & Wang, Fang & Zhu, Ruitai, 2021. "Finite-time adaptive neural control of nonlinear systems with unknown output hysteresis," Applied Mathematics and Computation, Elsevier, vol. 403(C).
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