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Automatic control of ship motion conducting search in open waters

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this work a search operation support system is presented, which is an additional autopilot function block. Its task is to lead a vessel included in the search by the SAR services to the datum position on the basis of the data entered by the operator into the system and then automatically to search the indicated area according to the newly defined search pattern. The set goal can be achieved thanks to the autopilot that guides the ship along a given trajectory consisting of straight lines and arcs. High control accuracy is provided by the IMC control system using a relatively simple non-linear ship model. The simulation tests of the tanker model confirmed that the indicated search area can be precisely checked in a shorter time than when using the expanding square search pattern.
Rocznik
Tom
Strony
157--169
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
  • Gdynia Maritime University Department of Ship Automation, Morska 83-87, 81-225 Gdynia, Poland
Bibliografia
  • 1. Ai Y., J. Lu, L.-L. Zhang L-L (2015): The optimization model for the location of maritime emergency supplies reserve bases and the configuration of salvage vessel. Transportation Research Part Vol. 83,170–188.
  • 2. Azofra M., Pérez-Labajos C.A., Blanco B. (2007): Optimum placement of sea resources. Safety Sciencen Vol. 45 (9), 941–951.
  • 3. Banda O.A.V. (2015): A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland. Environmental Science & Technology. 49, 5301−5309, doi: 10.1021/es501777g.
  • 4. Burns R., Richter R. (1996): Neural-network approach to the control of surface ships. Control Eng. Practice, Vol. 4, No. 3, 411–416.
  • 5. Z. Burciu Z. (2010): Bayesian methods in reliability of search and rescue action. Polish Maritime Research. 4(67), Vol. 17, 72–78, 2010, doi: 10.2478/v10012-010-0039-76.
  • 6. Goerlandt F, Torabihaghighi, Kujala P.(2013): A model for evaluating performance and reliability of the voluntary maritime rescue system in the Gulf of Finland. 11th International Conference Probabilistic Safety, Reliability and Risk Analysis: Beyond the Horizon, Amsterdam, Netherlands. 2013, 1351–1356.
  • 7. Guoxiang L., Maofeng L., (2010): SARGIS: a GIS-based decision-making support system for maritime search and rescue’, International Conference on E-Business and E-Government, doi: 10.1109/ICEE.2010.398.
  • 8. H. N. Esfahani H.N., Szlapczynski R. (2019): Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle. Polish Maritime Research. No. 3, Vol. 26, 163–171, doi: 10.2478/pomr-2019-0057.
  • 9. Fang M.-C., Luo J.-H. (2007): On the track keeping and roll reduction of the ship in random waves using different sliding mode controllers. Ocean Engineering 34, 479–488.
  • 10. Fossen T.I. (2002): Marine control systems: guidance, navigation and control of ships, rigs and underwater vehicles. Marine Cybernetics. Trondheim. ISBN 82-92356-00-2.
  • 11. Frost J.R., Cooper D.C., Robe Q. (2003): Compatibility of Land SAR Procedures with Search Theory. U.S. Department of Homeland Security United States Coast Guard Operations (G-OPR) Washington, D.C. 20593-0001.
  • 12. Frost J.R.,. Stone L.D. (2001): Review of search theory: Advances and applications to search and rescue decision support. US Coast Guard Research and Development Center, Groton. 2001.
  • 13. Koopman B.O. (1946): Search and screening. OEG Report No. 56, The Summary Reports Group of the Columbia University Division of War Research, Alexandria, Virginia, Center for Naval Analyses. 1946.
  • 14. Koopman B.O. (1980): Search and screening: general principles with historical applications. Revised. New York, Pergamon Press.
  • 15. Kula K.S. ( 2015): Autopilot Using the Nonlinear Inverse Ship Model. Marine Navigation and Safety of Sea Transportation, CRC Press, ISBN: 978-1-138-02858-6, 101–108.
  • 16. Kula K.S.,Tomera M. (2017): Control system of training ship keeping the desired path consisting of straight-lines and circular arcs. TransNav Journal Vol. 11 No. 4. 2017, 711–719, doi: 10.12716/1001.11.04.19.
  • 17. IAMSAR Manual, IMO/ICAO-International Aeronautical and Maritime Search and Rescue Manual, Vol. III, Mission Co-ordination, London/Montreal. 2008.
  • 18. Li L. (2006): Rescue vessel location modeling. MSc thesis. Halifax, Canada, Dalhousie University, Department of Industrial Engineering.
  • 19. Liu Y., Bu R., Gao X. (2018): Ship Trajectory Tracking Control System Design Based on Sliding Mode Control Algorithm, Polish Maritime Research. No 3,Vol. 25, 26–34, doi: 10.2478/ pomr-2018-0093.
  • 20. Morari M., Zafiriou E (1989): Robust process control. Englewood Cliffs, NJ Prentice Hall, 1989, ISBN-13:978-0137821532.
  • 21. Nomoto K., Taguchi T., Honda K., Hirano S. (1957): On the steering qualities of ships. International Shipbuilding Progress 4, 354–370.
  • 22. Norrington L., Quigley J., Russel A., Van der Meer R. (2008): Modeling the reliability of search and rescue operations with Bayesian Networks. Reliability Engineering & System Safety Vol. 93(7), 940–949.
  • 23. Richter R., Burns R. (1993): An artificial neural network autopilot for small vessels. Proceedings of the 1st Conference of the UK Simulation Society, Edinburgh, 168–172.
  • 24. Stone L.D.(1989): Theory of optimal search. Military Applications Section. Operations Research Society of America, Arlington, Virginia, ORSA Books.
  • 25. Velasco F.J., López E.(2000): Predictive Control of Ship Steering Autopilots. 2nd International Congress on Maritime Technological Innovations and Research, Spain, 89–98.
  • 26. Witkowska A., R. Śmierzchalski (2012): Designing a ship course controller by applying the adaptive backstepping method. Int. J. Appl. Math. Comput. Sci., Vol. 22, No. 4, 985–997, doi: 10.2478/v10006-012-0073-y.
  • 27. Tomera M. (2018): Switching-Based Multi-Operational Control of Ship Motion. Akademicka Oficyna Wydawnicza EXIT. Warszawa.
  • 28. Tzeng. C.-Y. (1999): An internal model control approach to the design of yaw-rate-control ship-steering autopilot, IEEE Journal of Oceanic Engineering, Vol. 24, No. 4, pp. 507–513.
  • 29. Yang Y.S., Ren J.S. (2003): Adaptive fuzzy robust tracking controller design via small gain approach and its application. IEEE Transactions on Fuzzy Systems, 11, 783–795.
  • 30. Zeid I., Frost J.R. (2005) A decision support system for Canadian search and rescue operations’, European Journal of Operation Research. 162 3, 630–653.
  • 31. Zwierzewicz Z. (2015): The design of ship autopilot by applying observer-based feedback linearization. Polish Maritime Research 22(1), 16–21.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-94875564-c4f9-4bb6-8ceb-160780844b2e
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