Fuzzy Course Tracking Control of Unmanned Surface Vehicle with Actuator Input Quantization and Event-Triggered Mechanism

This paper discusses the course tracking control of unmanned surface vehicles with actuator input quantization and an event-triggered mechanism. The system control laws are designed based on the backstepping method, combining dynamic surface control technology to mitigate the computational complexity expansion of virtual control laws. A fuzzy logic system can be used to approximate the uncertainties in the control system. The control system’s control inputs are quantized by using uniform quantizers. Then, the event-triggered adaptive fuzzy quantization control method is introduced, which can reduce the frequency of control actions and effectively reduce the communication burden. The stability of the control system is rigorously proven using Lyapunov stability theory, ensuring that all signals in the closed-loop system remain bounded. Finally, simulation tests are used to show the algorithm’s efficiency and usefulness.