Dynamic surface sliding mode algorithm based on approximation for course-keeping control of ship

Abstract

In the paper, an original dynamic surface sliding mode control(DSSMC) method is proposed for course-keeping control of ship in the presence of modeling errors. To overcome the interference and enhance the robustness, the dynamic surface control (DSC) technique is modified by employing sliding mode control. The radial basis function neural network(RBFNN) approximation technique is used for approximating modeling errors, and then the minimum learning parameter(MLP) is used for reducing the computational burden. The controller guarantees that all the close-loop signals are uniform ultimate bounded (UUB), in the meantime, the tracking error is proved to be converging to a very small neighborhood of the prescribed trajectory. In the end, simulation researches are given to verify the effectiveness of the algorithm presented above.