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ZHU Man, WEN Yuanqiao, SUN Wuqiang, ZHANG Jiahui, HAHN Axel. A Review of Parameter Identification Methods for Ship Dynamic Models[J]. Journal of Transport Information and Safety, 2022, 40(5): 1-11. doi: 10.3963/j.jssn.1674-4861.2022.05.001
Citation: ZHU Man, WEN Yuanqiao, SUN Wuqiang, ZHANG Jiahui, HAHN Axel. A Review of Parameter Identification Methods for Ship Dynamic Models[J]. Journal of Transport Information and Safety, 2022, 40(5): 1-11. doi: 10.3963/j.jssn.1674-4861.2022.05.001
shu

A Review of Parameter Identification Methods for Ship Dynamic Models

doi: 10.3963/j.jssn.1674-4861.2022.05.001
  • 1.

    Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

  • 2.

    Sanya Science and Education Innovation Park of Wuhan University of Technology, Sanya 572025, Hainan, China

  • 3.

    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China

  • 4.

    Institute of Artificial Intelligent, Sunwin Intelligent Co., Ltd., Hefei 230000, China

  • 5.

    School of Navigation, Wuhan University of Technology, Wuhan 430063, China

  • 6.

    Computer Science, Carl-von-Ossietzky University of Oldenburg, Oldenburg 26121, Germany

  • Received Date: 2022-04-22
    Available Online: 2022-12-05
    Abstract
  • Developing a dynamic model with a high accuracy and reliability is essential for analyzing ship maneuverability and ensuring shipping safety. Compared with the existing three popular methods, including empirical, experimental and computational fluid dynamics (CFD), numerical parameter identification methods are practical, effective, and powerful solutions for dynamic modeling. However, it faces major challenges due to the influences from the following factors, such as strong nonlinear motion characteristics of ships, varying environmental interfer-ences, and the multiple internal and external uncertainties. This paper reviews the state-of-the-art of parameter identification of ship dynamic models from the following four critical perspectives, including the optimal input design related to the informative characteristics acquisition, the mathematical model of ship motion, parameter estimation algorithms, and the verification and validation of the identified models. Several critical problems are discussed including noise interference, parameter drift, parameter variation, and selection of evaluation indexes. Based on a comprehensive survey, two challenging issues are pointed out. Currently, there is no method available that can provide high-quality data covering motion characteristics over a wide area, and due to the complexity of the models, the parameter drift fluctuates and cannot be completely avoided. Potential research questions closely related to the parameter identification of ship dynamic models are discussed. For instance, ship dynamic data acquired and processed using robust estimation techniques or information fusion techniques is worthy to be addressed to provide high-quality data; robust online parameter identification based on the multi-innovation intelligent approach can be a valuable solution to real-time identification of ship dynamic models; and complex conditions, such as ships sailing in restricted waters, should to be examined.

     

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