Abstract

In this study, the crow search algorithm is used for the first time to address the parameter identification problem of the ship motion model in the autonomous navigation of ships. A target-oriented crow search algorithm (TO-CSA) is developed to use in this new search technique to identify model parameters, which greatly improves the speed of convergence, accuracy, and stability of the identification results. The main advantages of this approach over previous research are its improved computational accuracy and precise identification of ship parameters with fewer data or under specific sea conditions, which are in line with actual sailing scenarios. Additionally, the feasibility and efficiency of the created algorithm are evaluated by simulations and actual ship trials, and the engineering applicability of this research is shown based on the effectiveness of ship direction autopilot control.

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