Skip to main content
SpringerLink
Log in

System identification modelling of ship manoeuvring motion based on ε-support vector regression

  • Article
  • Published:
Journal of Hydrodynamics Aims and scope Submit manuscript

Abstract

Based on the ε-support vector regression, three modelling methods for the ship manoeuvring motion, i.e., the white-box modelling, the grey-box modelling and the black-box modelling, are investigated. The 10°/10°, 20°/20° zigzag tests and the 35° turning circle manoeuvre are simulated. Part of the simulation data for the 20°/20° zigzag test are used to train the support vectors, and the trained support vector machine is used to predict the whole 20°/20° zigzag test. Comparison between the simula- ted and predicted 20°/20° zigzag test shows a good predictive ability of the three modelling methods. Then all mathematical models obtained by the modelling methods are used to predict the 10°/10° zigzag test and o35 turning circle manoeuvre, and the predicted results are compared with those of simulation tests to demonstrate the good generalization performance of the mathematical models. Finally, the modelling methods are analyzed and compared with each other in terms of the application conditions, the prediction accuracy and the computation speed. An appropriate modelling method can be chosen according to the intended use of the mathematical models and the available data for the system identification.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. IMO. Standards for ship manoeuvrability[S]. Resolution MSC.137(76), International Maritime Organization (IMO), 2002.

    Google Scholar 

  2. ABKOWITZ M. A. Measurement of hydrodynamic characteristic from ship maneuvering trials by system identi-fication[J]. Transactions of Society of Naval Architects and Marine Engineers, 1980, 88: 283–318.

    Google Scholar 

  3. HWANG W. Y. Application of system identification to ship maneuvering[D]. Doctoral Thesis, Boston, USA: Massachusetts Institute of Technology, 1980.

    Google Scholar 

  4. ÅSTRÖM K. J., KÄLLSTRÖM C. G. Identification of ship steering dynamics[J]. Automatica, 1976, 12(1): 9–22.

    Article  Google Scholar 

  5. ZHOU W. W., BLANKE M. Identification of a class of nonlinear state-space models using RPE techniques[J]. IEEE Transactions on Automatic Control, 1989, 34(3): 312–316.

    Article  MathSciNet  Google Scholar 

  6. RHEE K. P., LEE S. Y. and SUNG Y. J. Estimation of manoeuvring coefficients from PMM test by genetic algorithm[C]. Proceedings of International Symposium and Workshop on Force Acting on a Manoeuvring Vessel. Val de Reuil, France, 1998, 77–87.

    Google Scholar 

  7. BHATTACHARYYA S. K., HADDARA M. R. Parametric identification for nonlinear ship manoeuvring[J]. Journal of Ship Research, 2006, 50(3): 197–207.

    Google Scholar 

  8. PEREZ T., FOSSEN T. I. Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data[J]. Ocean Engineering, 2011, 38(2–3): 426–435.

    Article  Google Scholar 

  9. HADDARA M. R., WANG Y. Parametric identification of manoeuvring models for ships[J]. International Shipbuilding Progress, 1999, 46(445): 5–27.

    Google Scholar 

  10. LUO W., ZOU Z. Parametric identification of ship maneuvering models by using support vector machines[J]. Journal of Ship Research, 2009, 53(1): 19–30.

    Google Scholar 

  11. LUO Wei-lin, ZOU Zao-jian. Elimination of simulta neous drift and sensitivity analysis in the hydrodynamic modeling of ship manoeuvring[J]. Journal of Shanghai Jiaotong University, 2008, 42(8): 1358–1362(in Chinese).

    Google Scholar 

  12. ZHANG Xin-guang, ZOU Zao-jian. Identification of Abkowitz model for ship manoeuvring motion using ε-support vector regression[J]. Journal of Hydrodynamics, 2011, 23(3): 353–360.

    Article  Google Scholar 

  13. XU Feng, ZOU Zao-jian and YIN Jian-chuan et al. Parametric identification and sensitivity analysis for autonomous underwater vehicles in diving plane[J]. Journal of Hydrodynamics, 2012, 24(5): 744–751.

    Article  Google Scholar 

  14. SUTULO S., GUEDES SOARES C. An algorithm for offline identification of ship manoeuvring mathematical models from free-running tests[J]. Ocean Engineering, 2014, 79: 10–25.

    Article  Google Scholar 

  15. RAJESH G., BHATTACHARYYA S. K. System identification for nonlinear maneuvering of large tankers using artificial neural network[J]. Applied Ocean Research, 2008, 30(4): 256–263.

    Article  Google Scholar 

  16. MOREIRA L., GUEDES SOARES C. Dynamic model of manoeuvrability using recursive neural networks[J]. Ocean Engineering, 2003, 30(13): 1669–1697.

    Article  Google Scholar 

  17. VAPNIK V. N. The nature of statistical learning theory[M]. New York, USA: Springer Verlag, 2000.

    Book  Google Scholar 

  18. FOSSEN T. I. Handbook of marine craft hydrodynamics and motion control[M]. New York, USA: John Wiley and Sons, 2011.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Xue-gang Wang  (王雪刚), Zao-jian Zou  (邹早建) & Xian-rui Hou  (侯先瑞)

  2. CCCC Fourth Harbor Engineering Institute Co., Ltd., Guangzhou, 510230, China

    Xue-gang Wang  (王雪刚)

  3. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Zao-jian Zou  (邹早建)

  4. Wuhan Second Ship Design and Research Institute, Wuhan, 430064, China

    Feng Xu  (徐锋)

Authors
  1. Xue-gang Wang  (王雪刚)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zao-jian Zou  (邹早建)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xian-rui Hou  (侯先瑞)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng Xu  (徐锋)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zao-jian Zou  (邹早建).

Additional information

Project supported by the National Natural Science Foun- dation of China (Grant No. 51279106), the Special Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110073110009).

Biography: WANG Xue-gang (1983-), Male, Ph. D.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Xg., Zou, Zj., Hou, Xr. et al. System identification modelling of ship manoeuvring motion based on ε-support vector regression. J Hydrodyn 27, 502–512 (2015). https://doi.org/10.1016/S1001-6058(15)60510-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1016/S1001-6058(15)60510-8

Key words

Search

Navigation