At present, the problems of underactuated, nonlinearity, and poor real-time performance are common in the research of ship motion control methods. The modeling of ship dynamics is one of the key points in ship controller design This paper uses Gaussian process regression in machine learning to identify ship model, in which an empirical ship maneuvering is used to generate state information data sets for regression training, which reduces the computational cost by using only low data volume for training. This approach avoids the calculation of hydrodynamic derivatives in the traditional mechanism modeling process and simplifies to optimize a small number of hyperparameters of the kernel function in Gaussian regression. Finally, the accuracy and robustness of the regression model are tested by cross-validation. Simulation results show that Gaussian process regression can be accurately used to identify nonparametric dynamic systems of ships.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Dynamic system identification of underactuated ship dynamics based on Gaussian process regression


    Beteiligte:
    Zhang, Pei (Autor:in) / Liu, Jialun (Autor:in) / Xie, Lingli (Autor:in) / Li, Shijie (Autor:in)


    Erscheinungsdatum :

    22.10.2021


    Format / Umfang :

    4446629 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Dynamics Analysis and Tracking Control of Underactuated Offshore Ship-To-Ship Crane System

    Luan, Guangrui / Zhang, Menghua / Ning, Donghong | Springer Verlag | 2025


    Ship control motion forecasting method and system based on local Gaussian process regression

    OUYANG ZILU / ZOU LU / LIU JINZHOU et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Identification of Hydrodynamic Derivative and Motion Modeling of Underactuated Ship Based on CFD

    Yuan, Shouzheng / Liu, Zhilin / Zheng, Linhe | British Library Conference Proceedings | 2019


    Extraction of Ship Route Using Gaussian Process Regression for Passenger Ships

    Liu, Zhao / Gong, Zhenyu / Zhang, Mingyang et al. | IEEE | 2023