Event-triggered trajectory tracking control of underactuated surface vessels with performance-improving mechanisms under input saturation and actuator faults

This paper deals with the improvement for the tracking performance of underactuated surface vessels (USVs) under input saturation and actuator faults. The neural networks (NNs) are used to reconstruct the dynamic uncertainty of the ship, and an adaptive law is designed to compensate the adverse effects of external unknown disturbances and bias faults on the system. To improve the tracking performance of the system, a nonlinear link is added in the design process of the control scheme to adjust the system error feedback, and the finite-time control (FTC) technology is used to further improve the steady-state performance and transient performance of the system. In addition, to solve the problem of communication resource limitation, an event-triggered mechanism for switching thresholds is introduced, which reduces the update frequency of controller signals. Based on the above techniques, a trajectory tracking control scheme with a performance improvement mechanism is designed. A rigorous stability analysis is provided for the control scheme using Lyapunov stability theory. Finally, the effectiveness of the control scheme is verified by two sets of simulations.