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Waypoint path controller for ships

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Języki publikacji
EN
Abstrakty
EN
The paper presents and discusses tests of a waypoint controller used to sail a ship along the desired route. The planned desired route for the moving ship is given as a set of waypoints connected with straight lines. The ship's control is based on the rudder blade deflection angle as a commanded parameter. The task of the controller is to determine the rudder angle which will allow the ship to sail along the desired route segment. The controller algorithm consists of two parts, the first of which is used for controlling the ship motion along linear segments of the desired route, while the second part is used when changing to the next route segment. A switching mechanism is designed to choose the relevant part of the control algorithm. The quality of operation of the ship motion control algorithm was tested on the training ship Blue Lady, at the Ship Handling Research and Training Centre located on the lake Silm at Kamionka near Iława, Poland.
Twórcy
autor
  • Gdynia Maritime University, Gdynia, Poland
autor
  • Gdynia Maritime University, Gdynia, Poland
Bibliografia
  • 1. Ahmed Y.A, & Hasegawa K. 2016. Fuzzy reasoned waypoint controller for automatic ship guidance. Proceedings of the 10th IFAC Conference on Control Applications in Marine Systems (CAMS), pp. 604-609. Trondheim, Norway.
  • 2. Amerongen J.V. & Nauta Lemke H.R.V. 1986. Recent development in automatic steering of ships. Journal of Navigation, 39(3): 349-362.
  • 3. Baker B., Qian C. & Nowak B. 2013. A combined speed and finite-time yaw controller for an underactuated unmanned surface vessel using way-point navigation. Proceedings of International Conference on Mechatronic and Embedded Systems and Applications (MESA). Portland, Oregon, USA
  • 4. Bertin D. 1998. Track-keeping controller for a precision manoeuvring autopilot. Proceedings of the IFAC Conference Control Application in Marine Systems (CAMS), pp. 155-160. Fukuoka, Japan,
  • 5. Chocianowicz W. & Pejaś J. 1982. Adaptive control system for steering the ship along the desired trajectory – based on the optimal control and filtering theory. Proceedings of Control Applications in Marine Systems (CAMS), pp. 319335. Genova, Italy.
  • 6. Davidson K.S.M. & Schiff L.I. 1946. Turning and course keeping qualities, Transactions of Society of Naval Architects Marine Engineers, 54: 152-190.
  • 7. Do K.D. & Pan J. 2003. Global waypoint tracking control of underactuated ships under relaxed assumption. Proceedings of the 42nd IEEE International Conference on Decision and Control (CDC), vol. 2, pp. 1244-1249. Maui, Hawaii, USA.
  • 8. Fossen T.I. 2011. Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons.
  • 9. Fredriksen E. & Pettersen K.Y. 2006. Global k-expotential way-point maneuvering of ships: Theory and experiments. Automatica, 42(4): 677-687
  • 10. Gierusz W. 2001. Simulation model of the shiphandling training boat Blue Lady. Control Application in Marine Systems 2001, Katebi R. (Ed.), pp. 255-260. Proceedings of IFAC Conference on Control Application in Marine Systems (CAMS). Glasgow, Scotland.
  • 11. Gierusz W., Nguyen Cong V. & Rak A. 2007. Maneuvering control and trajectory tracking of very large crude carrier, Ocean Engineering, 34(7): 932-945.
  • 12. Holzhüter T. 1990. A high precision track controller for ships, Proceedings of the 11th IFAC World Congress, pp. 118-123, Tallin, Estonian USSR.
  • 13. Kallstrom C.G. 1982. Identification and adaptive control applied to ship steering. PhD thesis, Lund Institute of Technology.
  • 14. Kula K.S. 2015. Model-based controller for ship trackkeeping using neural network. Proceedings of the 2nd IEEE International Conference on Cybernetics (CYBCONF), pp. 178-183. Gdynia, Poland.
  • 15. Kula K.S. & Tomera M. 2017. Control system of training ship keeping the desired path consisting of straight-lines and circular arcs. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 11(4): 711-719.
  • 16. Lazarowska A. 2016. A trajectory base method for ship’s safe path planning. Procedia Computer Science, 96: 1022 – 1031. Proceedings of the 20th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES2016. York, UK.
  • 17. Lisowski J. 2016. Analysis of methods of determining the safe ship trajectory. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 10(2): 223-228
  • 18. MathWorks 2019. Technical computing software for engineers and scientists. The MathWorks, Inc., http://www.mathworks.com.
  • 19. Messer A.C. & Grimble M.J. 1993. Introduction to robust ship track-keeping control design. Transactions of Instrumental Measurement and Control, 15(3): 104-110
  • 20. Miller A. & Rybczak M. 2015. Methods of controller synthesis using linear matrix inequalities and model predictive control. Scientific Journals of the Maritime University of Szczecin, 43(115): 22-28.
  • 21. Morawski L. & Pomirski J. 1998. Ship track-keeping: experiments with a physical tanker model. Control Engineering Practice, 6(6):763-769.
  • 22. Nomoto K., Taguchi T., Honda K. & Hirano S. 1957. On the steering Qualities of Ships. Technical Report, International Shipbuilding Progress, 4(35): 354-370.
  • 23. Pettersen K. & Lefeber E. 2001. Way-point tracking control of ships. Proceedings of 40th IEEE Conference on Decision and Control (CDC), pp. 940–945. Orlando, Florida, USA.
  • 24. Śmierzchalski R. & Łebkowski A. 2002. Moving objects in the problem of path planning by evolutionary computation. Neural Networks and Soft Computing, Rutkowski L. (Ed.), pp. 382-386. Proceedings of the sixth IEEE International Conference on Neural Networks and Soft Computing. Zakopane, Poland.
  • 25. Velagic J., Vukic Z. & Omerdic E. 2003. Adaptive fuzzy ship autopilot for track-keeping. Control Engineering Practice, 11(4): 433-443.
  • 26. Vukic Z., Omerdic E. & Kuljaca L. 1998. Improved fuzzy autopilot for track-keeping, Proceedings of IFAC Conference on Control Application in Marine Systems (CAMS), pp. 135-140. Fukuoka, Japan.
  • 27. Witkowska A. & Śmierzchalski R. 2018. Adaptive backstepping tracking control for an over-actuated DP marine vessel with inertia uncertainties, International Journal of Applied Mathematics and Computer Science, 28(4): 679-693
  • 28. Yu C. & Xiang X. 2017. Fuzzy-based way-point tracking control of autonomous marine vehicles with input saturation. Proceedings of the 36th Chinese Control Conference (CCC), 4836-4840. Dalian, China.
  • 29. Zhang Y., Hearn G.E. & Sen P. 1996. A Neural Network Approach to Ship Track-Keeping Control. IEEE Journal of Ocean Engineering, 21(4): 513-527.
  • 30. Zhuo Y. & Guo C. 2013. Underactuated ship way-points track control using repetitive learning neurofuzzy. Proceedings of the 25th Chinese Control and Decision Conference (CCDC), pp. 248-252. Guiyang, China.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-df2607ac-a621-4ebf-bfe6-0984cadb8dd9
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