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Event-triggered bipartite consensus for multi-agent systems subject to multiplicative and additive noises

Author

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  • Du, Yingxue
  • Wang, Yijing
  • Zuo, Zhiqiang
  • Zhang, Wentao

Abstract

This paper investigates the bipartite consensus problem in mean square sense for multi-agent systems subject to multiplicative and additive noises using the event-triggered strategy. Since the control gain is time-varying and agent-dependent, the implementation of event-triggered control may cause desynchrony of the control gain and the time-variation of Laplacian matrix. Moreover, the coexistence of antagonistic information and multiplicative noise gives rise to the difficulty of regarding the error system as the deterministic counterpart. To cope with these challenges, the boundedness of each agent’s states is first formulated. Based on it, a criteria for mean square bipartite consensus with event-triggered mechanism is derived by utilizing the semi-decomposition method. Finally, one example is given to show the validity of the event-triggered control protocol.

Suggested Citation

  • Du, Yingxue & Wang, Yijing & Zuo, Zhiqiang & Zhang, Wentao, 2022. "Event-triggered bipartite consensus for multi-agent systems subject to multiplicative and additive noises," Applied Mathematics and Computation, Elsevier, vol. 429(C).
    • Handle: RePEc:eee:apmaco:v:429:y:2022:i:c:s0096300322003095
    DOI: 10.1016/j.amc.2022.127235
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    References listed on IDEAS

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    1. Lu, Jianquan & Guo, Xing & Huang, Tingwen & Wang, Zhen, 2019. "Consensus of signed networked multi-agent systems with nonlinear coupling and communication delays," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 153-162.
    2. He, Xiaoyan & Wang, Qingyun & Yu, Wenwu, 2015. "Distributed finite-time containment control for second-order nonlinear multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 509-521.
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    Cited by:

    1. Luo, Mei & Wang, JinRong & Meng, Deyuan, 2023. "Stochastic convergence problems on switching networks: An event-triggered method," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    2. Kairui Chen & Zhangmou Zhu & Xianxian Zeng & Junwei Wang, 2023. "Distributed Observers for State Omniscience with Stochastic Communication Noises," Mathematics, MDPI, vol. 11(9), pages 1-14, April.

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