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<p>As a typical nonlinear system, mobile robots have been widely used in various applications. However, the application of wireless techniques makes networked mobile robots (NMRs) vulnerable to cyber-attacks, which may significantly degrade their control performance. Therefore, a resilient model predictive control (MPC) strategy is proposed for NMRs under false data injection (FDI) attacks. First of all, a hierarchical game-based resource allocation framework is designed to reduce the adverse effects of FDI attacks. Specifically, the upper-level game determines the number of important control input samples to be protected, and the lower-level game allocates the limited controller resources to protect these important control signals. Then, an event-based updating mechanism is developed under FDI attacks to reduce unnecessary computational burden. Based on these components, a resilient MPC algorithm is established. The algorithm’s feasibility and the closed-loop stability of the NMR are rigorously analyzed. Finally, simulations and experiments on mobile robots are conducted to verify the effectiveness of the proposed method.</p>

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Hierarchical game-based resilient MPC for networked mobile robot under FDI attacks

  • 期刊论文

  • 发表日期：

    2026年7月29日

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  • Yuxiang Li,
  • Ning He,
  • Dangtong He,
  • Lepeng Wang,
  • Fengjiao Hu,
  • Ningchang Liu

摘要

As a typical nonlinear system, mobile robots have been widely used in various applications. However, the application of wireless techniques makes networked mobile robots (NMRs) vulnerable to cyber-attacks, which may significantly degrade their control performance. Therefore, a resilient model predictive control (MPC) strategy is proposed for NMRs under false data injection (FDI) attacks. First of all, a hierarchical game-based resource allocation framework is designed to reduce the adverse effects of FDI attacks. Specifically, the upper-level game determines the number of important control input samples to be protected, and the lower-level game allocates the limited controller resources to protect these important control signals. Then, an event-based updating mechanism is developed under FDI attacks to reduce unnecessary computational burden. Based on these components, a resilient MPC algorithm is established. The algorithm’s feasibility and the closed-loop stability of the NMR are rigorously analyzed. Finally, simulations and experiments on mobile robots are conducted to verify the effectiveness of the proposed method.