| Abstract:In complex marine environments, unmanned vessel navigation is susceptible to the coupling effects of multiple sources of disturbances such as non-stationary wind, waves, and currents. Its dynamic behavior exhibits strong nonlinearity, time-varying, and chaotic characteristics, leading to problems such as delayed response and incomplete feature extraction in the stability prediction method based on linear assumptions, making it difficult to achieve accurate perception and active fault-tolerant control of navigation status. Therefore, a prediction and fault-tolerant control system for unmanned ship navigation stability based on chaotic time series analysis is designed. After inputting stability prediction and control instructions into the shore based simulation control platform, the inertial measurement unit collects roll, pitch, and heave motion data of the unmanned ship based on these instructions. The stability prediction unit adopts the chaotic time series analysis method to accurately capture the nonlinear dynamic characteristics of unmanned ships from their motion data, and then predict the roll angle, pitch angle, and heave acceleration to determine the navigation stability of unmanned ships. The fault-tolerant controller is based on the obstacle Lyapunov function, combined with predicted roll angle, pitch angle, and heave acceleration data, to design a fault-tolerant control law for the stability of unmanned ship navigation. Then, the control instructions are calculated through an encoder and sent to the driver to drive the power device to control the navigation state of the unmanned ship. The simulation experiment results show that the system can accurately predict the roll angle, pitch angle, and heave acceleration of unmanned ships during navigation, achieving effective prediction of navigation stability. Under different wind speed conditions, the maximum Hill inequality coefficient predicted for the stability of the system is about 0.18, indicating that its prediction accuracy is high and it can effectively complete the fault-tolerant control task of unmanned ship navigation stability. |
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