Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper describes the use of matrix game theory for the synthesis of safe control of a ship in collision situations. An analysis of the sensitivity of the ship control algorithm to the inaccuracy of process state information and changes in its parameters was presented. Sensitivity characteristics were compared on the example of the navigational situation in the Kattegat Strait for good and restricted visibility at sea.
Rocznik
Tom
Strony
527--532
Opis fizyczny
Bibliogr. 20 poz., rys.
Twórcy
autor
- Gdynia Maritime University, Gdynia, Poland
Bibliografia
- 1. Eslami M. 1994. Theory of sensitivity in dynamic systems. Berlin: Springer-Verlag. - doi:10.1007/978-3-662-01632-9
- 2. Isaacs R. 1965. Differential games. New York: John Wiley and Sons.
- 3. Kula K. 2014. Cascade control system of fin stabilizers. Proc. XIX Conference Methods and Models in Automation and Robotics, MMAR, Miedzyzdroje: 868-873.
- 4. Lazarowska A. 2017. A new deterministic approach in a decision support system for ship’s trajectory planning. Expert Systems with Applications, Vol. 71: 469-478. - doi:10.1016/j.eswa.2016.11.005
- 5. Łebkowski A.: Design of an Autonomous Transport System for Coastal Areas. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 12, No. 1, doi:10.12716/1001.12.01.13, pp. 117-124, 2018
- 6. Lisowski J. 2012. Game control methods in avoidance of ships collisions. Polish Maritime Research Vol.19, No. 1: 3-10. - doi:10.2478/v10012-012-0016-4
- 7. Lisowski J. 2013. Sensitivity of computer support game algorithms of safe ship control. International Journal of Applied Mathematics and Computer Science. Vol. 23, Issue 2: 439-446. - doi:10.2478/amcs-2013-0033
- 8. Lisowski J. 2014. Comparison of dynamic games in application to safe ship control. Polish Maritime Research, Vol. 21, No. 3: 3-12. - doi:10.2478/pomr-2014-0024
- 9. Lisowski J. 2014. Optimization-supported decision-making in the marine game environment. Solid State Phenomena, Vol. 210: 215-22. - doi:10.4028/www.scientific.net/SSP.210.215
- 10. Lisowski J.: Analysis of Methods of Determining the Safe Ship Trajectory. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 10, No. 2, doi:10.12716/1001.10.02.05, pp. 223-228, 2016
- 11. Malecki J. 2013. Fuzzy track-keeping steering design for a precise control of the ship. Solid State Phenomena, Vol. 197: 140-147. - doi:10.4028/www.scientific.net/SSP.196.140
- 12. Modarres M. 2006. Risk analysis in engineering. Boca Raton: Taylor and Francis Group.
- 13. Mohamed-Seghir M. 2016. Computational intelligence method for ship trajectory planning. Proc. XXI Conference Methods and Models in Automation and Robotics, MMAR, Miedzyzdroje: 636-640.
- 14. Nisan N., Roughgarden T., Tardos E. & Vazirani V.V. 2007. Algorithmic game theory. New York: Cambridge University Press. - doi:10.1017/CBO9780511800481
- 15. Osborne M.J. 2004. An introduction to game theory. New York: Oxford University Press.
- 16. Rosenwasser E. & Yusupov R. 2000. Sensitivity of automatic control systems. Boca Raton: CRC Press.
- 17, Szlapczynski R. & Szlapczynska J. 2016. An analysis of domain-based ship collision risk parameters. Ocean Engineering, Vol. 126: 47-56. - doi:10.1016/j.oceaneng.2016.08.030
- 18. Tomera M. 2012. Nonlinear observers design for multivariable ship motion control. Polish Maritime Research, Vol. 19, Issue 1: 50-56. - doi:10.2478/v10012-012-0023-5
- 19. Wierzbicki A. 1977. Models and sensitivity of control systems (in Polish). Warszawa: WNT.
- 20. Zak A. 2013. Trajectory tracking control of underwater vehicles. Solid State Phenomena, Vol. 196: 156-166. - doi:10.4028/www.scientific.net/SSP.196.156
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3e5ddd02-ba95-41ca-b3d0-5f271615bbd2