Robust adaptive asymptotic trajectory tracking control for underactuated surface vessels subject to unknown dynamics and input saturation

In this paper, a robust adaptive control scheme is proposed for the trajectory tracking control of underactuated surface vessels (USVs) subject to unknown dynamics, external disturbances and input saturation. First, a coordinate transformation is introduced to deal with the underactuation problem of the USV. A Gaussian error function and an adaptive neural network (NN) are adopted to approximate the saturation function and the unknown dynamics, respectively. Then, an adaptive robust integral of the sign of the error (RISE) feedback term is introduced in feedback control design to compensate the NN and saturation approximation residual errors and unknown external disturbances. On the basis of the above, a robust adaptive trajectory tracking control law is proposed incorporating a coordinate transformation, Gaussian error function and NN into RISE method. In addition, the adjustable-online adaptive feedback gain reduces the conservativeness of the control design. The theoretical analysis indicates that the designed robust adaptive control law can force USVs to track the desired trajectory while guaranteeing the asymptotic tracking performance. Simulation results verify the effectiveness of the novel robust adaptive trajectory tracking control scheme.