Parameters Optimization-Based Tracking Control for Unmanned Surface Vehicles

In this paper, a type of tracking controller on the basis of parameters optimization was proposed for unmanned surface vehicles (USVs). Taking into account the unique nonlinear and large inertia characteristics of USVs, an iterative sliding mode control (ISMC) was adopted to construct the controller including the USVs’ main engine speed controller to determine the longitudinal velocity and the steering controller to control the lateral displacement. In designing, the hyperbolic tangent function with the saturation characteristic is introduced to design the output feedback control law of nonlinear iterative sliding mode. Then, the differential evolution algorithm (DEA) is applied to construct the parameters optimization system for acquiring the optimal parameters of the proposed controller, and the control quality with adaptive ability and robustness of the optimized controller is achieved. It is verified by computer experiments that the optimized controller realizes the tracking control for USV under interference; meanwhile, compared with the iterative sliding mode controller, the control performance of the controller is better and the robustness of that is stronger.