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Application of optimal control theory based on the evolution strategy (CMA-ES) to automatic berthing (part: 2)

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Abstract

Currently, accelerated research on automation is involved in most fields associated with vehicle manufacturing. In the area of autonomous operation of marine vehicles, automatic berthing remains a problem due to the nonlinearity of the low-speed maneuvering model, poor control of the vessel at low speed, and collision with berth danger. A previous study on off-line automatic berthing reveals frequent switching of the propeller revolution direction, which is impractical and must be prevented in case of a diesel engine. In this study, to overcome this problem, a new variable for the time to switch the propeller revolution direction is introduced and optimized. Also, we establish a more robust off-line control method for optimizing the required time and the final ship attitude by enhancing the objective function. Since the method provided here is still an off-line control method, its applicability to on-line control must consider the external force uncertainty and modeling error. The set of the optimal control input and trajectory obtained in this study, however, are applicable as an initial candidate for on-line predictive control modeling. Furthermore, the trajectory can serve as the desired path in a path-tracking problem.

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Acknowledgements

This study was supported by a Grant-in-Aid for Scientific Research from the Japan Society for Promotion of Science (JSPS KAKENHI Grant # 19K04858). The study also received assistance from JFY2018 Fundamental Research Developing Association for Shipbuilding and Offshore (REDAS) in Japan. The authors are thankful to Enago (www.enago.jp) for reviewing the English language.

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Authors and Affiliations

  1. Department of Naval Architecture and Ocean Engineering, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0971, Japan

    Atsuo Maki & Umeda Naoya

  2. Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8573, Japan

    Youhei Akimoto

  3. RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, 103-0027, Japan

    Youhei Akimoto

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  1. Atsuo Maki
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  2. Youhei Akimoto
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  3. Umeda Naoya
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Correspondence to Atsuo Maki.

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Maki, A., Akimoto, Y. & Naoya, U. Application of optimal control theory based on the evolution strategy (CMA-ES) to automatic berthing (part: 2). J Mar Sci Technol 26, 835–845 (2021). https://doi.org/10.1007/s00773-020-00774-x

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  • DOI: https://doi.org/10.1007/s00773-020-00774-x

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