Dynamic surface control for tracking of unmanned surface vessel with prescribed performance and asymmetric time-varying full state constraints

In this paper, a novel prescribed performance and full state constraints dynamic surface control (PP&FSC-DSC) scheme is proposed for trajectory tracking of unmanned surface vessel (USV) with model uncertainties, unknown nonlinear disturbances and full state and input constraints. Firstly, the restricted system with inequality constraints is transformed into the system with equality constraints by the modified asymmetric barrier Lyapunov function (MABLF) and then combined with the prescribed performance function, the vessel position tracking error meets the prescribed performance. Secondly, owing to use the dynamic surface technique and introduce an auxiliary dynamic system (ADS), the double advantages are established, i.e., the negative effects of the differential operation for the intermediate control law and input saturation of the intermediate control law are avoided. Thirdly, the model uncertainties are approximated by the neural network (NN), and the NN approximation error and unknown nonlinear disturbances is adaptively estimated. Finally, according to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded (SGUUB). The trajectory can be maintained with prescribed tracking performance and the full state can be constrained. The effectiveness of the proposed control protocol is validated by the simulation results.

Automated summary

In this paper, a novel dynamic surface control scheme is proposed for trajectory tracking of unmanned surface vessel. The proposed scheme considers model uncertainties, unknown nonlinear disturbances, and full state and input constraints. The effectiveness of the control protocol is validated through simulations.