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DOI
Warianty tytułu
Języki publikacji
Abstrakty
This paper describes an application of the dynamic programming method to determine the safety of one’s own ship trajectory during encounter of other ships. A dynamic model of the process, with kinematic constraints of state and determined by a three-layer artificial neural network has been used for the development of control procedures. Non-linear activation functions in the first and second layers may be characterised by a tangent curve while the output layer is of a sigmoidal nature. The Neural Network Toolbox of the Matlab software has been used to model the network. The learning process used an algorithm of backward propagation of the error with an adaptively selected learning step. The considerations have been illustrated through an example implemented in a computer simulation using the algorithm for the determination of the safe ship trajectory in situations of encounter of multiple ships, recorded on the ship’s radar screen in real navigational situation in the Kattegat Strait.
Rocznik
Tom
Strony
91--97
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
- Gdynia Maritime University 83 Morska St., 81-225 Gdynia, Poland
Bibliografia
- 1. Bellman, R.E. (1957) Dynamic programming. New York: Princeton University Press.
- 2. Bist, D.S. (2000) Safety and security at sea. Oxford-New Delhi: Butter Heinemann.
- 3. Colley, B.A., Curtis, R.G. & Stockel, C.T. (1983) Manoeuvring times, domains and arenas. Journal of Navigation 36. pp. 324–328.
- 4. Cross, S.J. (1994) Objective assessment of maritime simulator training. Proc. of the Int. Conf. the Development and Implementation of International Maritime Training Standards, Malmo.
- 5. Davie, P.V., Dove, M.J. & Stockel, C.T. (1980) A computer simulation of marine traffic using domains and arenas. Journal of Navigation 33. pp. 215–222.
- 6. Goodvin, E.M. (1975) A statistical study of ship domains. Journal of Navigation 28. pp. 328–334.
- 7. Guenin, B., Konemann, J. & Tuncel, L. (2014) A gentle introduction to optimization. United Kingdom, Cambridge University Press.
- 8. Hertz, J., Krogh, A. & Palmer, R.G. (1991) Introduction to the theory of neural computation. Addison-Wesley Publ.
- 9. Hunt, K.J., Irwin, G.R. & Warwick, K. (1995) Neural network engineering in dynamic control systems.Advances in industrial control series. Springer.
- 10. Kouemou, G. (2009) Radar technology. Chapter 4 by Józef Lisowski: Sensitivity of safe game ship control on base information from ARPA radar, Croatia, In-tech, pp. 61–86.
- 11. Leondes, C.T. (1998) Control and dynamic systems, neural network systems techniques and applications. Vol. 7. Academic Press.
- 12. Lew, A. & Mauch, H. (2007) Dynamic programming – a computational tool. Springer
- 13. Modarres, M. (2006) Risk analysis in engineering. Boca Raton: Taylor & Francis Group.
- 14. Speyer, J.L. & Jacobson, D.H. (2010) Primer on optimal control theory. Toronto: SIAM.
- 15. Wiśniewski, B. (2011) Integrated problem of ship route planning. Silesian University of Technology, Archives of Transport System Telematic 4, 4. pp. 58–64.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d8c95647-7bae-4c6a-ad5f-0055a1207393