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Privacy preservation-based dynamic event-triggered bipartite consensus strategy for nonlinear multi-agent systems with unknown mismatched disturbances

Author

Listed:
  • Wu, Ziwei
  • Xu, Ning
  • Zhang, Liang
  • Zhao, Ning
  • Song, Guangjing

Abstract

In this paper, a dynamic event-triggered bipartite consensus control strategy is proposed for a class of nonlinear multi-agent systems (MAS) with mismatched disturbances. The core idea of this strategy is to divide the subjects into two groups. In order to avoid the leakage of system information, a privacy preservation mechanism is introduced. By constructing a mask function, the state of the system is protected to enhance data confidentiality while guaranteeing system stability. Meanwhile, a disturbance observer is constructed to estimate the composite disturbance term consisting of mismatched external disturbances and approximation errors, which ensures system performances. In addition, due to limited communication bandwidth of the networked nonlinear system, a distributed event-triggered mechanism is introduced to reduce the communication burden, and the Zeno behavior is excluded. It is shown from stability analysis that signals of the overall closed-loop system can be guaranteed to be bounded. Finally, the effectiveness of the proposed strategy is verified by a numerical example.

Suggested Citation

  • Wu, Ziwei & Xu, Ning & Zhang, Liang & Zhao, Ning & Song, Guangjing, 2026. "Privacy preservation-based dynamic event-triggered bipartite consensus strategy for nonlinear multi-agent systems with unknown mismatched disturbances," Applied Mathematics and Computation, Elsevier, vol. 515(C).
    • Handle: RePEc:eee:apmaco:v:515:y:2026:i:c:s0096300325005715
    DOI: 10.1016/j.amc.2025.129846
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    References listed on IDEAS

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