Neural adaptive robust control of underactuated marine surface vehicles with input saturation

•A new saturated tracking controller is proposed for underactuated surface vehicles.•A new second-order error dynamic model is developed to design the controller.•Generalized saturation functions are used to limit amplitude of control signals.•A neural adaptive robust controller is used to compensate model uncertainties.•The tracking performance is improved for large initial tracking errors.

This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications.