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Fully distributed self-triggered secure consensus for nonlinear multiagent systems with sequential communication link scaling attacks

Author

Listed:
  • Zhao, Miao
  • Xi, Jianxiang
  • Wang, Le
  • Wang, Cheng
  • Zheng, Yuanshi

Abstract

This paper proposes an adaptive distributed event-triggered secure consensus control scheme for achieving fully distributed self-triggered secure consensus control of nonlinear multiagent systems with sequential communication link scaling attacks. Firstly, attacks on the communication link for nonlinear multiagent systems are modeled by sequential communication link scaling attacks, which include communication link attacks or faults, deception attacks, DoS attacks, and sequential scaling attacks, etc. Based on an event-triggered control mechanism, the impacts of attack intervals on triggering sequences are analyzed. Then, an adaptive event-triggered secure consensus control scheme is proposed, which contains an edge-based adaptive event-triggered protocol and a dynamic event-triggered function for each agent, and can be implemented in a fully distributed and self-triggered fashion. Furthermore, by utilizing the Lipchitz condition and the properties of the Laplacian potential, sufficient conditions for nonlinear multiagent systems with sequential communication link scaling attacks to achieve secure consensus control are given, where the attack frequency and duration that the system can render are presented. Finally, the Zeno phenomenon is excluded and a simulation example is provided.

Suggested Citation

  • Zhao, Miao & Xi, Jianxiang & Wang, Le & Wang, Cheng & Zheng, Yuanshi, 2025. "Fully distributed self-triggered secure consensus for nonlinear multiagent systems with sequential communication link scaling attacks," Applied Mathematics and Computation, Elsevier, vol. 490(C).
    • Handle: RePEc:eee:apmaco:v:490:y:2025:i:c:s0096300324006465
    DOI: 10.1016/j.amc.2024.129185
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    References listed on IDEAS

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    1. Tian, Meng & Dong, Zhengcheng & Wang, Xianpei, 2021. "Reinforcement learning approach for robustness analysis of complex networks with incomplete information," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    2. Li, Weihua & Zhang, Huaguang & Wang, Wei & Cao, Zhengbao, 2022. "Fully distributed event-triggered time-varying formation control of multi-agent systems subject to mode-switching denial-of-service attacks," Applied Mathematics and Computation, Elsevier, vol. 414(C).
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