ADAPTIVE ROBUST OUTPUT FEEDBACK TRAJECTORY TRACKING CONTROL FOR SHIPS WITH INPUT NONLINEARITIES

作者：Xia, Guoqing^*; Zhao, Ang; Wu, Huiyong; Liu, Ju

来源：International Journal of Robotics and Automation, 2016, 31(4): 341-353.

DOI：10.2316/Journal.206.2016.4.206-4529

• Surface ships
• trajectory tracking
• output feedback
• RBF neural network
• fuzzy logic system (FLS)
• input nonlinearities

In this paper, we consider the problem of trajectory tracking for fully actuated dynamic positioning (DP) ships in the presence of parametric uncertainties, unknown external disturbances and input nonlinearities. A linear dynamic compensator is designed to compensate the linear part in the system, while the parameters are obtained through the pole assignment technique. The robust neural adaptive control improves the robustness against the unknown nonlinear parts. As it is difficult to measure velocities of the ships accurately, a convenient observer is proposed. An auxiliary system and a fuzzy logic system (FLS) based dead-zone compensator are designed separately to cope with the saturation and unknown dead-zone characteristics of actuators, followed by an integration of these two compensation methods into the final control scheme. Through the Lyapunov's direct method, the adaptive updating laws of both RBF weights and FLS parameters are derived, and the ultimate boundedness of the closed-loop signals is shown. Simulation results are demonstrative of the excellent performance of the proposed control scheme.

• 出版日期2016
• 单位哈尔滨工程大学; 中国电子科技集团公司第三十八研究所