Trajectory tracking control for a marine surface vessel with asymmetric saturation actuators

This paper investigates the problem of trajectory tracking control for an unmanned marine surface vessel (MSV) with external disturbances and asymmetric saturation actuators. An adaptive radial basis function neural network (RBFNN) is constructed to provide an estimation of the unknown disturbances and is applied to design the trajectory tracking controller through a backstepping technique. To handle the effect of nonsmooth asymmetric saturation nonlinearity, a Gaussian error function-based continuous differentiable asymmetric saturation model is employed such that the backstepping technique can be used in the control design. It is proved that all the states in the closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of origin by appropriately choosing design parameters. Simulation results and comparisons illustrate the effectiveness of the proposed controller and its robustness to external disturbances and asymmetric saturation actuators.