Dynamic Event-Triggered Model Predictive Control for Nonlinear Discrete Cyber-Physical Systems With Hybrid Attacks

This study presents a novel approach to dynamic event-triggered model predictive control (MPC) for nonlinear discrete-time cyber-physical systems (CPSs) subject to simultaneous hybrid denial of service (DoS) and deception attacks on the sensor-to-controller and controller-to-actuator communication channels. The proposed method introduces a dynamic event-triggered mechanism (DETM) with a predetermined offset to optimize communication efficiency in bandwidth-limited systems. Furthermore, a mechanism for detecting attacks has been developed to ensure the integrity of transmitted information, thereby mitigating the impact of hybrid attacks. Theoretical conditions are established to ensure the input-to-state practical stability of the closed-loop system using the proposed method. Finally, simulation cases are presented to validate the superiority of the proposed method in comparison to existing approaches in scenarios where CPSs encounter similar hybrid attacks.