Event-Triggered Based Trajectory Tracking Control of Under-Actuated Unmanned Surface Vehicle With State and Input Quantization

This paper is dedicated to the trajectory tracking control of under-actuated unmanned surface vessel (USV) with state and input quantization. In terms of kinematics, a distributed guidance law is introduced to track the time-varying trajectory of USV. In terms of kinetics, a fuzzy adaptive quantization control method rooted in an event-triggered mechanism is proposed. Uncertainties within the ship model are estimated through a fuzzy logic system, and a linear analytical model is employed to elucidate the input quantization process. This approach reduces the actuator's execution frequency, alleviates the communication burden and conserves valuable communication resources. The boundedness of the internal signals and quantization errors in the closed-loop system are substantiated by presenting some theoretical lemmas. Furthermore, the stability of the proposed control strategy is proved through Lyapunov stability theory. Finally, the effectiveness and feasibility of the proposed fuzzy adaptive quantization control strategy based on event-triggered mechanism are verified by simulation experiments.