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<p>This study focuses on the model predictive control (MPC) problem of nonlinear cyber-physical systems under joint deception attacks. A Stackelberg game framework is developed to illustrate the strategic interactions among sensors, controllers, and actuators. Three linear quadratic performance indices are employed to characterize the behaviors of both the attackers and the controller. The attacker’s objective is to maximize the performance index associated with the attack, while the controller seeks to minimize the overall performance index of the system. By leveraging the first-mover advantage inherent in the Stackelberg game, a balance of performance indices is achieved through MPC and approximate dynamic programming (ADP). This approach theoretically ensures the stability of the closed-loop system’s input states and is validated by numerical examples.</p>

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Stackelberg game-based model predictive control design for cyber-physical systems under joint deception attacks

  • 期刊论文

  • 发表日期：

    2025年5月26日

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  • Hongchao Song,
  • Zhenlei Wang

摘要

This study focuses on the model predictive control (MPC) problem of nonlinear cyber-physical systems under joint deception attacks. A Stackelberg game framework is developed to illustrate the strategic interactions among sensors, controllers, and actuators. Three linear quadratic performance indices are employed to characterize the behaviors of both the attackers and the controller. The attacker’s objective is to maximize the performance index associated with the attack, while the controller seeks to minimize the overall performance index of the system. By leveraging the first-mover advantage inherent in the Stackelberg game, a balance of performance indices is achieved through MPC and approximate dynamic programming (ADP). This approach theoretically ensures the stability of the closed-loop system’s input states and is validated by numerical examples.