Resilient MPC With Switched Cost Functions for Cyber-Physical Systems Against DoS Attacks

This article introduces a resilient model predictive control (MPC) approach for constrained cyber-physical systems (CPSs) in the presence of bounded disturbances and denial-of-service (DoS) attacks. An attacker aims to disrupt the communication channel between the controller and actuator (C-A) by deploying adversarial jamming signals. A resilient MPC algorithm is designed, where switching between different cost functions is considered and the control input sequences optimized are used to compensate for information loss caused by DoS attacks. We demonstrate that under certain conditions on the duration of DoS attacks and system parameters, the closed-loop system can be guaranteed to be uniformly ultimately bounded (UUB) in the attack scenario. Moreover, in the nonattack scenario, it exhibits robust asymptotic stability. By properly setting tightened constraints and cost functions, the recursive feasibility of the optimization problem can be ensured for any admissible attack scenario and disturbances realization. The maximum duration of DoS attacks that can be tolerated in the C-A channel is derived by feasibility analysis. Finally, the effectiveness of the designed algorithm is validated through a simulation example, which includes comparisons with two other algorithms.