Robust adaptive fault-tolerant control for unmanned surface vehicle via the multiplied event-triggered mechanism.

This paper investigates a novel robust adaptive fault-tolerant control algorithm for the path-following activity of the unmanned surface vehicle (USV) via the multiplied event-triggered mechanism. An improved multiplied event-triggered condition is designed by employing the estimate model with a concise form. Thus, the burden-some problem is released, especially for the channel from sensors to the controller. Besides, two discrete adaptive parameters are constructed to stabilize the perturbation caused by the gain constraint and actuator faults. The model uncertainties and the practical disturbance are compensated by utilizing neural networks (NNs) approximation, in which the weight updating is reduced with the robust neural damping technique. With the direct Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability can be guaranteed for the closed-loop system. Finally, both the simulation and the physical vehicle-based experiments are illustrated to verify the effectiveness of the algorithm. • A robust fault-tolerant control algorithm is proposed for unmanned surface vehicle. • The adaptive parameters are updated online to compensate for unknown actuator faults. • An improved multiplied event-triggered condition is designed with a concise form. • It can evade the unnecessary information transmission of the onboard control network. [ABSTRACT FROM AUTHOR]