Adaptive Fault‐Tolerant Tracking Control for Underactuated USVs: A Prescribed Performance Approach

ABSTRACT In this paper, an adaptive fault‐tolerant tracking control scheme is proposed for underactuated unmanned surface vehicles (USVs). Compared to the traditional prescribed performance control, the limitation of the initial error constraint is eliminated through error transformation, which is a great benefit for actual engineering applications. Neural networks are employed to approximate the unknown nonlinear terms, effectively improving uncertainty rejection capabilities. Moreover, to solve the problem of intermittent multiple faults, a new adaptive fault‐tolerant control strategy is proposed, maintaining the short‐term and long‐term operational efficiency of the USV system, even when several actuators experience malfunctions. Based on the Lyapunov stability theory, it is demonstrated that all signals in the closed‐loop system are uniformly ultimately bounded. Moreover, it should be noticed that the developed method can also address the challenge of sporadic actuator malfunctions. Ultimately, the scheme's efficacy and superiority are confirmed by the outcomes of the simulation studies.