Output-Constrained Point-to-Point Tracking of Underactuated Surface Vessel with Uncertainties

This paper considers the point-to-point tracking control problem of an underactuated surface vessel (USV) with output constraints and uncertainties. The controller design is based on backstepping algorithm. Barrier Lyapunov function (BLF) is used to address the output constraints. In addition, a radial basis function neural network (RBFNN) is constructed to provide an estimation and compensation of the unknown disturbances. It is proved that under the proposed control, the constraints will never be violated, and all closed-loop signals are bounded. Simulation results and comparisons illustrate the effectiveness and advantages of the proposed controller.