Robust trajectory tracking control for underactuated autonomous surface vessels with uncertainty dynamics and unavailable velocities

This paper solves the trajectory tracking problem for underactuated autonomous surface vessels in the presence of uncertainty dynamics and unavailable velocities. A robust controller is proposed by employing a neural network, command filtered backstepping method, and adaptive control method. Moreover, all tracking errors are guaranteed to be uniformly ultimately bounded on the basis of the Lyapunov Theorem. The findings of the study are summarized as follows: (i) The uncertainty dynamics of the control system are estimated and approximated by the neural network and state predictors, which allows the designed controller to be easily applied in practice. (ii) To accurately acquire the velocities of the control system, a neuro-adaptive observer is proposed to obtain the unavailable velocities. (iii) A filtered compensation loop is built to decrease filtered signal error, which is caused by the second-order filter. Finally, simulations are performed to verify the robustness and effective tracking performance of the proposed control scheme in consideration of external disturbances.