Extended prescribed performance fault-tolerant control of autonomous surface vessels using event-triggered inputs

This paper investigates the prescribed performance control (PPC) problem of autonomous surface vessels with actuator faults. To ensure the error performance satisfaction and control simplicity, barrier Lyapunov function is utilized to establish PPC framework, in which the initial tracking constraint that inherently exists in the traditional method is removed via error-shifting transformation. To prevent the performance violation in the event of actuator faults, a computationally efficient adaptive fault-tolerant controller is derived using event-triggered inputs, which not only permits aperiodic control update to save communication resources, but also greatly reduces the online computation burden because of avoiding the iterative update of neural networks weight. Through Lyapunov stability analysis, it is proven that all signals in the closed-loop system are semi-globally uniformly ultimately bounded, and both position and yaw angle tracking errors can converge to their prescribed regions in finite time from any initial values. Finally, the effectiveness and superiority of the proposed scheme are verified by simulation examples.