Resilient model predictive reset control for cyber-physical systems subject to hybrid attacks

This paper investigates a resilient model predictive reset control strategy for cyber-physical systems (CPSs) with state and input constraints under hybrid attacks. Jamming attacks are modeled using Stackelberg game theory and result in packet loss . A malicious false data injection attacker randomly injects fault signals to manipulate the control inputs. A channel reset strategy is proposed to ensure that the auxiliary controller can safely transmit the prediction signals to the buffer for storage. The primary controller exerts its utility in the absence of a jamming attack, whereas once the false data attack is detected, compensation and computation are performed using predictive values computed by the auxiliary controller, which can improve the system control performance. The predictive signals computed by the auxiliary controller are only used when an attack is detected in the MPC strategy proposed in this article. Furthermore, the feasibility of the proposed reset control strategy is discussed. Finally, the effectiveness and benefits of the model predictive reset control strategy proposed in this paper are verified through a numerical example.