Event-Triggered Adaptive Practical Fixed-Time Trajectory Tracking Control for Unmanned Surface Vehicle

This brief investigates the fixed-time trajectory tracking control problem for unmanned surface vehicle with unknown dynamics based on command filtered backstepping technique and stability theory. Distinct from existing results where execution is periodic computational burden overlarge, a novel event-triggered adaptive practical fuzzy controller designed to guarantee of closed-loop system (CLS), aperiodically updated only at event-sampled instants. Theoretical analysis proves that errors can diminish an arbitrarily small neighborhood origin within fixed time interval prescribed convergence free initial states under proposed method. Finally, simulation are provided demonstrate validity developed approach.