Adaptive Optimization Control of Unmanned Surface Vessel with Thruster Fault

In view of both unknown dynamics and thruster fault, an adaptive model predictive-based fault-tolerant control scheme was proposed for an unmanned surface vessel(USV). Firstly, the dynamics model of the USV with faults was established, and the unknown nonlinear dynamics and external disturbance in the dynamics model were formed into a lumped nonlinear function. The unknown part in the dynamics was approximated by the neural network. In order to achieve high performance and accurate tracking of the desired trajectory, an adaptive autonomous fault-tolerant control strategy was designed by combining model predictive control and backstepping control, with the index function of control input and state error as variables. Then, based on Lyapunov stability theory, it was proven that all signals in the closed-loop system were bounded. The control strategy constructed under this framework could not only compensate for the influence of actuator faults and unknown nonlinear dynamics on the system but also ensure that the tracking error of the system converges to the ideal precision. Simulation results verify the effectiveness and rationality of the proposed method.