To deal with the problems of horizontal trajectory tracking control of underactuated unmanned surface vehicle (USV) in the presence of model uncertainties and unknown ocean currents

a robust nonlinear trajectory tracking controller for underactuated USV was proposed based on the backstepping method and adaptive technique. For the model uncertainties of underactuated USV

the adaptive neural network technique was employed to estimate and compensate the unknown model uncertainties. Then

the derivatives of virtual control variables were obtained by dynamic surface control method. The control law was simple in structure and easy to be realized in engineering

and it greatly reduced the complexities of the traditional backstepping method. For the disturbances of unknown time-varying currents

an observer was designed to estimate the velocity of unknown time-varying currents. Next

based on Lyapunov’s direct method

it was proved that the designed controller could ensure that the motion trajectory converged to the expected value

and that all signals of the trajectory tracking closed-loop control system were finally uniformly bounded. Lastly

under the condition of limited control input

in order to verify the tracking performance of the controller

the circular trajectory was selected as the reference trajectory. Simulations were carried out and results show that the controller could accurately track the desired trajectory and had strong robustness for model uncertainties and unknown time-varying currents. In addition

the unknown functions of the system were effectively estimated and compensated by adaptive neural network technique

which verified the effectiveness of the proposed tracking control scheme.