Event-triggered robust adaptive control for path following of the URS in presence of the marine practice

Abstract This note investigates an event-triggered robust adaptive control for path following of the unmanned robot sailboat (URS) by employing the proportional integral sliding mode manifold and the robust neural damping technique in presence of marine practice. The dominant assignment of this note can be summarized into three points: (1) The double-layer virtual guidance is developed to generate the reference signal for three navigation conditions (i.e., the upwind sailing, the downwind sailing and the crosswind sailing). That can enhance the navigating automatism of the URS while the tacking and the gybing. (2) The system uncertainties are approximated by the radial basis function neural networks (RBF-NNs). To further simplify the controller form, the robust neural damping technique has been introduced to evade the updated information of the neural weights. Furthermore, the input saturation of the closed-loop control system is tackled by constructing the auxiliary variable in the control design. (3) The communication burden in the channel from the controller to the actuator can be reduced for merits of the event-triggered rule. Besides, the system chattering, caused by the marine disturbances has also been reduced through the proportional integral sliding mode manifold and gain-related adaptive law. The tracking errors of the closed-loop control system will converge to a compact set, and all the signals satisfy the semi-global uniformly ultimately bounded (SGUUB) stability. Finally, the effectiveness and the robustness of the proposed algorithm have been demonstrated via the numerical simulations under the simulated marine environment.