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This paper proposes a distributed \( H_{\infty } \) fusion filtering method based on Unmanned Surface Vessels (USVs) for Cyber-Physical Systems (CPSs) under False Data Injection (FDI) attacks. Firstly, a model of CPSs based on USVs is constructed, and real-valued matrix inequalities are formulated based on linear and nonlinear functions to guarantee mean-square exponential stability of the filtering error system. Secondly, a Lyapunov functional is introduced to determine the optimal parameters for local filters, guaranteeing robustness in dynamic environments. Thirdly, a distributed \( H_{\infty } \) fusion filter is devised by integrating the performance indices of local filters to counteract FDI attacks. Ultimately, simulation experiments are conducted and the results confirm the feasibility of the proposed method.

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Distributed \( H_{\infty } \) Fusion Filtering for Cyber-Physical Systems with FDI Attacks

  • 会议论文

  • 发表日期：

    2026年

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  • Xiaolin Xu,
  • Li Liu,
  • Hongyong Yang,
  • Guanlong Deng,
  • Zheng Liu,
  • Xin Hu

摘要

This paper proposes a distributed \( H_{\infty } \) fusion filtering method based on Unmanned Surface Vessels (USVs) for Cyber-Physical Systems (CPSs) under False Data Injection (FDI) attacks. Firstly, a model of CPSs based on USVs is constructed, and real-valued matrix inequalities are formulated based on linear and nonlinear functions to guarantee mean-square exponential stability of the filtering error system. Secondly, a Lyapunov functional is introduced to determine the optimal parameters for local filters, guaranteeing robustness in dynamic environments. Thirdly, a distributed \( H_{\infty } \) fusion filter is devised by integrating the performance indices of local filters to counteract FDI attacks. Ultimately, simulation experiments are conducted and the results confirm the feasibility of the proposed method.