As the global economy and shipping industry continue to expand, transportation vessels are increasingly moving towards larger scales. This shift necessitates enhanced control performance and maneuverability for ships. This paper aims to bridge research gaps in the domain of collision risk management based on maritime rules, specifically focusing on intelligent collision avoidance strategies for underactuated merchant ships. The research integrates advancements by employing the MMG separation modeling and examining various algorithms to enhance autonomous navigation. By combining the improved artificial potential field method with the ship domain model, this study conducts ship simulation navigation experiments under different operational conditions. The primary objective is to develop a robust collision avoidance system that adheres to international maritime collision avoidance regulations, thereby increasing safety and efficiency in maritime operations. Future research will continue to refine these models and explore real-world applications to improve the reliability and practicality of collision management systems for commercial ships.
Aiming at the path tracking problem of unmanned surface vehicle, a sliding mode control algorithm enhanced with adaptive control technology is proposed. Adaptive control technology is used to predict the boundary value of unknown external environment interference. In order to improve the robustness of the system and the convergence rate of path tracking, the optimization algorithm is designed based on the hyperbolic tangent function control reaching law. A new double power combination function is proposed as the control law to design the sliding mode control algorithm to control the forward and steering of unmanned surface vehicle. The chattering phenomenon caused by sliding mode control is solved effectively and the convergence speed of path tracking is improved. The curve fitting method is utilized to realize the effective tracking of any planned flight path. The simulation results demonstrate that the proposed adaptive sliding mode control algorithm is able to ensure unmanned surface vehicle track the upper reference path accurately under the time-varying disturbance of wind, waves and currents. In additional, the adaptive sliding mode control algorithm embedded an approach control law, called new double power function, is confirmed that has strong robustness and fast convergence rate of path tracking.
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