Dynamic Event-Based Predefined-Time Adaptive Fuzzy Trajectory Tracking Control of Underwater Tracked Robot With Specified Accuracy

This paper investigates the robust adaptive predefined-time trajectory tracking control issue for underwater tracked robot with unknown track slipping and unknown dead-zone input. Fuzzy logic system (FLS) is employed to approximate the unknown nonlinear dynamic. A pair of parameter adaptive laws is designed to counteract the effects of unknown track slipping. To ensure that the trajectory tracking error converges to a specified accuracy within a predefined time, a predefined-time performance function is designed. Then, a barrier Lyapunov function (BLF) is constructed by embedding the performance function to avoid the singularity problem. In addition, a disturbance observer is constructed to observe and compensate for hydrodynamic disturbances present in the system dynamics, while a dynamic event-triggered mechanism is proposed to alleviate the computational load and reduce the actuator update frequency. Under the adaptive backstepping recursive design framework, a predefined-time event-triggered robust adaptive trajectory tracking control algorithm with performance constraints is proposed, which ensures system stability while enforcing predefined performance on the tracking error. Finally, the effectiveness and superiority of the proposed control scheme are validated through comparative simulations and data analysis.