Adaptive Neural Network Control of a Marine Surface Vessel with Output Constrains

In this article, an adaptive neural network (NN) trajectory tracking control is proposed for a marine surface vessel with output constraints and uncertainties. The second-order linear tracking differentiator was employed to cope with differential blast problem, an adaptive NN is adopted to estimate the uncertainty models and unknown disturbances, and an asymmetric barrier Lyapunov function (BLF) is used to handle the output constrains problems. Moreover, it is proven that the multiple output limits are never violated, the asymptotic tracking can be implemented, and all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). A numerical simulation are demonstrated the availability of the proposed methods.