Abstract
In this paper, wave inversion is innovatively applied to the path following control of unmanned ship for the first time. At the same time, the performance constraint problem and input saturation of the control system are considered, and the model uncertainty problem of the system is solved by improving the RBF algorithm. Firstly, the system identification method is used to obtain the wave information in real time and quickly based on the ship motion response under the current sea condition, and the disturbance compensation is carried out in the unmanned ship control system. Secondly, in order to ensure the safety and stability of the unmanned ship during navigation, the performance constraints of the unmanned ship path following control system are carried out. In addition, considering the external disturbance and model uncertainty, the RBF neural network control algorithm based on the predictor estimation error is designed, which greatly improves the transient performance of the controller. Finally, the stability analysis and simulation comparison test verify the correctness and feasibility of the proposed control strategy.
Published Version
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