Event-based adaptive control for unmanned surface vehicle subject to deception attacks

This note focuses on the course-keeping control problem for unmanned surface vehicles (USVs) in presence of communication burden and deception attacks. The robust adaptive event-triggered control algorithm has been proposed by fusing the event-triggered mechanism(ETM) and adaptive compensated methods. In the control algorithm, deception attacks happen at communication networks are compensated by constructing attack adaptive learning parameters. Besides, the transmission burden is effectively alleviated for merit of the input-based event-triggered rule. Finally, the theoretical stability is proofed by the Lyapunov theorem and the well performance has been obtained through numerical simulation in presence of the time-varying disturbances.