Practical Finite-Time Event-Triggered Trajectory Tracking Control for Underactuated Surface Vessels With Error Constraints

This paper proposes a robust trajectory tracking control method for underactuated unmanned surface vessels (USVs) with input saturation based on a relative threshold event-triggered mechanism (ETM), prescribed performance and finite-time convergence. First, to address the challenges posed to controller design by the nondiagonal inertia matrix, coordinate transformation technology is adapted to change the vessel position. An asymmetric smooth saturation function is employed to address the input saturation problem. Second, an adaptive neural network (NN) is developed to approximate the uncertain nonlinear dynamics and external environmental disturbances. Third, the performance function constraints are integrated into the tan-type barrier Lyapunov function (BLF) to greatly enhance the robustness of the system by combining with the finite-time convergence property. In addition, the dynamic surface control (DSC) technique is employed to address the differential explosion problem. Subsequently, a relative threshold ETM is incorporated into the controller to reduce the communication burden. The rationality and feasibility of the proposed algorithm are confirmed by theoretical analysis and numerical simulations.

Automated summary

This paper proposes a robust trajectory tracking control method for underactuated unmanned surface vessels, combining relative threshold event-triggered mechanism, prescribed performance and finite-time convergence. The proposed method addresses the challenges posed by the nondiagonal inertia matrix and input saturation problem, and incorporates adaptive neural network for approximating uncertain dynamics. In addition, the method enhances robustness by integrating performance function constraints and dynamic surface control, and reduces communication burden by incorporating relative threshold event-triggered mechanism.