Robust Neural Network‐based Tracking Control for Unmanned Surface Vessels under Deferred Asymmetric Constraints

In this article, the constraints on unmanned surface vessels are imposed after a certain time after the system operation. Based on the shift function, this article proposes an asymmetric barrier Lyapunov function and achieves the control scheme with deferred and asymmetric full‐state constraints. In addition, radial basis function neural network and an antiwindup compensator are adopted for the problems of uncertainties and input saturation. The simulation results demonstrate the feasibility of the proposed control strategies.