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Automatic berthing control under wind disturbances and its implementation in an embedded system

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Abstract

This paper proposes a practical algorithm and its implementation of automatic berthing in wind disturbances environments. Berthing operation is one of the most complex tasks for seafarers. Automation of the highly burdensome berthing maneuver can be used to assist seafarers. In this study, we analyze the effect of wind disturbance on path following and propose a new path following control algorithm using a 2-DoF controller that introduces a feed-forward control. We also propose a method to reduce path deviation by introducing a runway in path planning. The effectiveness of the proposed method is verified by numerical simulations and shipboard tests using an experimental ship, and the proposed method shows higher performance under wind disturbance than the previous methods. The algorithm verified in this study is implemented as a PLC system, AutoBerth PLC. A PLC is an industrial computer, stable in operation. Using the AutoBerth PLC, we conducted an experiment of automatic berthing by an actual ship and confirmed that the system can be controlled faster and more stable than when controlled by a laptop. To realize a practical system, an alert function for the ODD, an alert function for fallback response regarding self-diagnosis of PLCs and communication monitoring functions were implemented as required functions in a maritime autonomous surface ship (MASS), and these functions were verified on the experimental ship.

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References

  1. International Maritime Organization (IMO). MSC.1/Circ.1638, Outcome of the regulatory scoping exercise for the use of maritime autonomous surface ships (MASS) (2021)

  2. Sawada R, Hirata K, Kitagawa Y, Saito E, Ueno M, Tanizawa K, Fukuto J (2021) Path following algorithm application to automatic berthing control. Journal of Marine Science and Technology 26:541

    Article  Google Scholar 

  3. SAE International. SAE J3016:2021, Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (2021)

  4. Ahmed YA, Hasegawa K (2013) Automatic ship berthing using artificial neural network trained by consistent teaching data using nonlinear programming method. Engineering Applications of Artificial Intelligence 26(10):2287

    Article  Google Scholar 

  5. Shuai Y, Li G, Cheng X, Skulstad R, Xu J, Liu H, Zhang H (2019) An efficient neural-network based approach to automatic ship docking. Ocean Engineering 191:106514

    Article  Google Scholar 

  6. Mizuno N, Kuboshima R (2019) Implementation and evaluation of non-linear optimal feedback control for ship’s automatic berthing by recurrent neural network, IFAC-PapersOnLine 52(21), 91 (2019), 12th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles CAMS

  7. Mizuno N, Uchida Y, Okazaki T (2015) Quasi real-time optimal control scheme for automatic berthing. IFAC-PapersOnLine 48(16):305

    Article  Google Scholar 

  8. Martinsen AB, Bitar G, Lekkas AM, Gros S (2020) Optimization-based automatic docking and berthing of asvs using exteroceptive sensors: Theory and experiments. IEEE Access 8:204974

    Article  Google Scholar 

  9. Maki A, Sakamoto N, Akimoto Y, Nishikawa H, Umeda N (2020) Application of optimal control theory based on the evolution strategy (CMA-ES) to automatic berthing. Journal of Marine Science and Technology 25(1):221

    Article  Google Scholar 

  10. Akimoto Y, Miyauchi Y, Maki A (2022) Saddle point optimization with approximate minimization oracle and its application to robust berthing control, ACM Trans. Evol. Learn. Optim. 2(1)

  11. Okuyama E, Igarashi K, Oda H, Miyazaki K, Ohtsu K, Okazaki T (2007) Guidance control of vessels using minimum time control, 2007 IEEE International Conference on Systems, Man and Cybernetics pp. 3650–3655

  12. Ohtsu K, Shoji K, Okazaki T (1995) Minimum time maneuvering of ship with wind disturbances, IFAC Proceedings Volumes 28(2), 338, 3rd IFAC Workshop on Control Applications in Marine Systems, Trondheim, Norway, 10-12 May

  13. Han S, Wang Y, Wang L, He H (2021) Automatic berthing for an underactuated unmanned surface vehicle: A real-time motion planning approach. Ocean Engineering 235:109352

    Article  Google Scholar 

  14. Piao Z, Guo C, Sun S (2019) Research into the automatic berthing of underactuated unmanned ships under wind loads based on experiment and numerical analysis, Journal of Marine Science and Engineering 7(9)

  15. Shimizu S, Nishihara K, Miyauchi Y, Wakita K, Suyama R, Maki A, Shirakawa S (2022) Automatic berthing using supervised learning and reinforcement learning. Ocean Engineering 265:112553

    Article  Google Scholar 

  16. Liu Y, Im N.k, Zhang Q, Zhu G (2022) Adaptive auto-berthing control of underactuated vessel based on barrier lyapunov function, Journal of Marine Science and Engineering 10(2)

  17. Miyoshi S, Ioki T (2021) Development of maneuvering system for realizing autonomous ships, Class NK Technical Journal (3)

  18. Inoue S, Mori H (2021) Development of automated ship operation technologies, Class NK Technical Journal (3)

  19. Kim YY, Choi KJ, Chung H, Han S, Lee PS (2014) A ship-to-ship automatic docking system for ocean cargo transfer. Journal of Marine Science and Technology 19:360

    Article  Google Scholar 

  20. International Electrotechnical Commission (IEC), IEC 62065:2014 Maritime navigation and radiocommunication equipment and systems - Track control systems - Operational and performance requirements, methods of testing and required test results. Standard 2.0, International Electrotechnical Commission (IEC) (2014)

  21. International Electrotechnical Commission (IEC), IEC 61131-3:2013 programmable controllers - part 3: Programming languages. Standard 3.0, International Electrotechnical Commission (IEC) (2013)

  22. Yasukawa H, Yoshimura Y (2014) Introduction of MMG standard method for ship maneuvering predictions. Journal of Marine Science and Technology 20:37

    Article  Google Scholar 

  23. Motora S (1959) On the measurement of added mass and added moment of inertia for ship motions. Journal of the Society of Naval Architects of Japan 1959(105):83

    Google Scholar 

  24. Motora S (1960) On the measurement of added mass and added moment of inertia for ship motions, part 2. added mass abstract for the longitudinal motions, Journal of the Society of Naval Architects of Japan 1960(106), 59

  25. Motora S (1960) On the measurement of added mass and added moment of inertia for ship motions, part 3. added mass for the transverse motions, Journal of the Society of Naval Architects of Japan 1960(106), 63

  26. Yoshimura Y, Nakao I, Ishibashi A (2009) Unified mathematical model for ocean and harbour manoeuvring, Proceedings of MARSIM2009 pp. 116–124

  27. Kitagawa Y, Tsukada Y, Miyazaki H (2015) A study on mathematical models of propeller and rudder under maneuvering with propeller reverse rotation. Proc. JASNAOE 20:117 (in Japanese)

    Google Scholar 

  28. Ueno M et al (2017) Researches on advanced technology for initial responses, reproduction, and analysis of marine accidents using the actual sea model basin and the bridge simulator for navigation risk. Papers of National Maritime Research Institute 17(1):1 (in Japanese)

    Google Scholar 

  29. Kose K, Yumuro A, Yoshimura Y (1981) Iii. concrete of mathematical model for ship manoeuvring., Proceedings of the 3rd symposium on ship maneuverability, Society of Naval Architects of Japan pp. 27–80, in Japanese

  30. Fujii H, Tuda T (1961) Experimental researches on rudder performance (2), Journal of the Society of Naval Architects of Japan pp. 31–42

  31. Kitamura F, Ueno M, Fujiwara T, Sogihara N (2017) Estimation of above water structural parameters and wind loads on ships. Ships and Offshore Structures 12(8):1100

    Article  Google Scholar 

  32. Monahan A.H (2006) The probability distribution of sea surface wind speeds. part I: Theory and seawinds observations, Journal of Climate 19(4), 497

  33. Seguro J, Lambert T (2000) Modern estimation of the parameters of the weibull wind speed distribution for wind energy analysis. Journal of Wind Engineering and Industrial Aerodynamics 85(1):75

    Article  Google Scholar 

  34. Yoshimura Y, Matsumoto Y (2011) Hydrodynamic force database with medium high speed merchant ships including fishing vessels and investigation into a manoeuvring prediction method. Journal of the Japan Society of Naval Architects and Ocean Engineers 14:63 (in Japanese)

    Article  Google Scholar 

  35. Tsukada Y, Sugui N, Ueda T, Kadoi H, Fujii I (1991) Experimentalstudieson improvement of propulsiveperformance for high speed passenger boat. Papers of Ship Research Institute 28(5):43 (in Japanese)

    Google Scholar 

  36. Fossen T (1994) Guidance and control of ocean vehicles

  37. Sarda EI, Qu H, Bertaska IR, von Ellenrieder KD (2016) Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances. Ocean Engineering 127:305

    Article  Google Scholar 

  38. Hane F (2012) Control technology for autopilot for vessels. Journal of The Society of Instrument and Control Engineers 51(11):1086

    Google Scholar 

  39. Bezanson J, Karpinski S, Shah V.B, Edelman A (2012) Julia: A fast dynamic language for technical computing, CoRR arXiv:abs/1209.5145

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Authors and Affiliations

  1. National Maritime Research Institute, 6-38-1, Shinkawa, Mitaka, Tokyo, 181-0004, Japan

    Ryohei Sawada, Koichi Hirata & Yasushi Kitagawa

  2. Osaka University, 2-1 Yamadaoka, Suita, Osaka, Japan

    Ryohei Sawada

Authors
  1. Ryohei Sawada
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  2. Koichi Hirata
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  3. Yasushi Kitagawa
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Correspondence to Ryohei Sawada.

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Sawada, R., Hirata, K. & Kitagawa, Y. Automatic berthing control under wind disturbances and its implementation in an embedded system. J Mar Sci Technol 28, 452–470 (2023). https://doi.org/10.1007/s00773-023-00934-9

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  • DOI: https://doi.org/10.1007/s00773-023-00934-9

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