Data-driven unmanned surface vehicles trajectory tracking adaptive control

Objectives A data-driven trajectory tracking control scheme is proposed for Unmanned Surface Vehicles (USV) with uncertain parameters. Methods Firstly, the USV kinematics subsystem is processed by the backstepping, and we can obtain the virtual control signal of the kinematics subsystem which ensure the accuracy of the system trajectory tracking. Secondly, the data-driven is used to deal with the USV dynamics subsystem to get the controller which reduces the impact of uncertainties such as unknown disturbances and reduce the complexity of controller design. Results The stability of the system is proved by analyzing the pseudo jacobian matrix and the convergence of the tracking error of dynamics and kinematics. Conclusions Simulation results show that the control strategy proposed in this paper can track the expected trajectory effectively, and the effectiveness of the control scheme is verified.