Adaptive Sliding Mode Control for Unmanned Surface Vehicle Trajectory Tracking Based on Event-Driven and Control Input Quantization

This primary study aims to optimize network resource utilization efficiency in marine control systems. A novel event-triggering condition is proposed to significantly reduce communication traffic, where the error norm is squared while the input norm remains linear. To simulate realistic environmental disturbances, bounded unknown parameters are incorporated. Within the networked transmission architecture, input quantization is introduced, enabling the design of a quantized feedback controller without prior knowledge of quantization parameters. By integrating the event-triggering mechanism with sliding mode control, a quantized feedback control system is developed. The closed-loop system’s stability is rigorously proven via Lyapunov theory, with guaranteed boundedness of trajectory tracking errors. Numerical simulations validate the effectiveness of the proposed method for marine vehicle trajectory control under environmental disturbances.