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Adaptive consensus of uncertain switched nonlinear multi-agent systems under sensor deception attacks

Author

Listed:
  • Ma, Yajing
  • Li, Zhanjie
  • Xie, Xiangpeng
  • Yue, Dong

Abstract

This paper addresses the consensus issue for a class of uncertain switched nonlinear multi-agent systems subject to unknown system parameters and sensor deception attacks. The actual data information is corrupted by attacks and cannot be used for the feedback control. To tackle the attacks, a set of novel auxiliary variables are introduced for the iterative design by the corrupted data. By considering the common effect of all the switching dynamics, the inherent interaction effects caused by unknown parameters, unpredictable switching and sensor deception attacks are transferred to two induced parameters. We then propose two adaptive laws to compensate the induced parameters. By constructing a common Lyapunov function, an adaptive consensus protocol is developed, under which the asymptotic output consensus of the considered uncertain systems is guaranteed regardless of deception attacks and arbitrary switching. An example is provided to illustrate the effectiveness of the established protocol.

Suggested Citation

  • Ma, Yajing & Li, Zhanjie & Xie, Xiangpeng & Yue, Dong, 2023. "Adaptive consensus of uncertain switched nonlinear multi-agent systems under sensor deception attacks," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008378
    DOI: 10.1016/j.chaos.2023.113936
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    References listed on IDEAS

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    Cited by:

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    2. Zhao, Xiao-Wen & Deng, Dong-Dong & Ge, Ming-Feng & Liu, Zhi-Wei, 2024. "Neural adaptive predefined-time formation tracking control of multiple Euler–Lagrange systems with switching topologies based on hierarchical mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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