欺骗攻击下弹性自触发模型预测控制

Aiming at solving the cyber security problem of self-triggered model predictive control (MPC) in cyber-physical systems under deception attacks, a resilient self-triggered MPC strategy based on the key data protection is proposed. Compared with the existing MPC methods, the proposed method only protects a small number of key control samples to ensure the stability of the system, thus effectively saving system resources. Firstly, the upper limit of the difference between the nominal and attacked states is analyzed based on the characteristics of self-triggered MPC and deception attacks, so as to quantitatively calculate the damages to the system caused by deception attacks. Then, the selection conditions of the key data are given based on the obtained upper limit of the state difference and Lyapunov stability theory. Finally, it is demonstrated that the controlled system can be operated stably under deception attacks when only key control samples are protected. Furthermore, the proposed algorithm is simulated based on the mobile robot and cart-damper-spring system, and the results show that the proposed algorithm can significantly save the protection resources, which verifies the effectiveness of the method.