Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode

摘要

Adaptive robust controllers are proposed for trajectory tracking and stabilization of underactuated surface vessels simultaneously in this paper. Hierarchical sliding mode is employed to deal with the underactuation of the model, and neural network is used as a tool for approximating unknown nonlinear function in the system; in this way, the robustness of the proposed controller is strengthened, and the chattering problem of sliding mode technique is relieved. The nonlinear damping terms of ship's model are considered which are neglected in many studies, and the time-varying disturbances are taken into account to test the robustness of the designed controllers. Stability is guaranteed by Lyapunov theorem, and the proof is given. Numerical simulations are implemented to demonstrate the effectiveness and the robustness of the designed controllers.