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This paper addresses the problem of trajectory tracking control of a surface vessel subject to parametric uncertainties, external disturbances, and thruster faults. A novel robust fault-tolerant tracking controller is developed by incorporating the radial basis function neural network and an adaptive control technique into the sliding mode control. It is shown that the designed controller is not only robust against environmental disturbances induced by waves and ocean currents, but also able to ensure that the surface vessel tracks the desired trajectory, without resorting to any knowledge of inertia parameters and despite the presence of thruster faults. In particular, exploiting a novel time-varying sliding mode manifold, the tracking errors are proved to converge to zero within a finite time, whose value can be pre-assigned by the designers according to the mission requirements. Numerical examples are carried out to testify the effectiveness of the proposed control algorithm.

Finite-Time Trajectory Tracking Fault-Tolerant Control for Surface Vessel Based on Time-Varying Sliding Mode