Intelligent Finite-Time Protocol-Based Stabilization for Networked UMV Systems With DoS Attacks

This study concentrates on the finite-time protocol-based stabilization for networked unmanned marine vehicle (UMV) systems with denial-of-service (DoS) attacks. To save limited communication resources, a novel event-driven protocol is proposed, in which Q-learning mechanism is adopted to adjust the threshold of the driven condition intelligently. In light of aperiodic DoS attacks, the corresponding switched system is constructed in light of the average dwell time strategy. Employing switching Lyapunov functional, sufficient conditions are made for finite-time boundedness of the UMV systems with disturbance, respectively, in which the relationship among the DoS parameter, the triggered parameter, the finite-time parameter, and the sampling period is accurately characterized. Moreover, the co-design approach of driven parameter and controller gain is proposed for the corresponding UMV systems. Finally, the benchmark UMV systems are shown to verify the effectiveness of the proposed strategy.