Warianty tytułu
Języki publikacji
Abstrakty
In cases when the navigational space of the manoeuvre performed by the ship is severely limited, the procedures making use of the rudder blade, propeller screw, and thrusters are very complicated. Such situations take place when the ship manoeuvres inside the harbour area and in those cases the structure of the control system is very complex. The article describes the algorithm of multivariable control of ship motion over the water surface, which makes use of the state vector consisting of 6 variables. Three of them, which are the position coordinates (x, y) measured by the DGPS system and the ship heading y measured by gyro-compass, were obtained experimentally. The three remaining variables, which are the velocities in surge u, sway v, and yaw r directions, were estimated by Kalman filter, KalmanBucy filter and extended Kalman filter, respectively. The control algorithms making use of these observers were examined using the training ship „Blue Lady” which was navigated on the lake Silm in Ilawa/Kamionka in the Ship Handling Research and Training Centre owned by the Foundation for Safety of Navigation and Environment Protection. The experimental results obtained using control systems with three observers were finally compared between each other
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Numer
Opis fizyczny
p.13-24,fig.,ref.
Twórcy
autor
- Department of Ship Automation, Faculty of Marine Electrical Engineering, Gdynia Maritime University, Morska 81-87, 81-225 Gdynia, Poland
Bibliografia
- 1. Strand J.P.: Nonlinear position control systems design for marine vessels, Ph.D. Thesis, Norwegian University Science and Technology, Deptment of Engineering Cybernetics, Trondheim, Norway, 1999.
- 2. Lindegaard K.-P.: Acceleration Feedback in Dynamic Positioning, Ph.D. Thesis, Norwegian University Science and Technology, Deptment of Engineering Cybernetics, Trondheim, Norway, 2003.
- 3. Fossen T.I., 1994. Guidance and control of ocean vehicles, John Wiley and Sons, Chichester, UK, 1994.
- 4. Amerongen J.V.: Adaptive Steering of Ships - Model Reference Approach, Automatica, Vol. 20, No 1, 1984, pp. 3-14.
- 5. Saelid S., Svanes T., Onshus T., Jensen N.A.: Design considerations, analysis and practical experince with an adaptive ship’s autopilot, In: Proceedings of the 9th IFAC World Congress, Budapest, Hungary, 1984, pp. 35-40.
- 6. Holzhuter T., Strauch H.: A Commercial Adaptive Autopilot for Ships: Design and Operational Experiences, In: Procedings of the 10th IFAC World Congress, Munch, Germany, 1987, pp. 226-230.
- 7. Amerongen J.V., Nauta Lemke H.R.V.: Recent development in automatic steering of ships, Journal of Navigation, Vol. 39, No 3, 1986, pp. 349-362.
- 8. Amerongen J.V., Land E.F.A.: An adaptive autopilot for track-keeping, Ship Operation Automation, III, Editor J. Vlietstra, North-Holland Publishing Company, 1980, pp. 105-114. 9. Chocianowicz W., Pejaś J.: Adaptive control system for steering the ship along the desired trajectory – based on the optimal control and filtering theory, In: Proceedings of the Control Applications in Marine Systems (CAMS-92), Genova, Italy, 1992, pp. 319-335.
- 10. Lu X.R., Jiang J.H., Huang Y.X.: Design of a selftuning adaptive track-keeping control system for ships, In: Proceedings of the International Conference on Modelling and Control of Marine Craft, University of Exeter, U.K., 1990, pp. 178-192.
- 11. Holzhüter T.: LQG approach for the high-precision track control of ships, IEE Proceedings: Control Theory Application, Vol. 144, No 2, 1997, pp. 121-127.
- 12. Bertin D.: Track-keeping controller for a precision manoeuvring autopilot, In: Proceedings of the IFAC Conference Control Application in Marine Systems (CAMS-98), Fukuoka, Japan, 1998, pp. 155-160.
- 13. Messer A.C., Grimble M.J.: Robust Track-keeping Control, Procedings of IFAC Workshop on Control Applications in Marine Systems (CAMS-92), Genova, Italy, 1992, pp. 371-380.
- 14. Vukic Z., Omerdic E., Kuljaca L.: Improved fuzzy autopilot for track-keeping, In: Proceedings of IFAC Conference on Control Application in Marine Systems (CAMS-98), Fukuoka, Japan, 1998, pp. 135-140.
- 15. Velagic J., Vukic Z., Omerdic E.: Adaptive fuzzy ship autopilot for track-keeping, Control Engineering Practice, Vol. 11, No 4, 2003, pp. 433-443.
- 16. Zhang Y., Hearn G.E., Sen P.: A Neural Network Approach to Ship Track-Keeping Control, IEEE Journal of Ocean Engineering, Vol. 21, No 4, 1996, pp. 513-527.
- 17. Galbas J.: Synthesis of precise ship steering system making use of thrusters, Ph.D. Thesis, Technical University of Gdańsk, Poland, 1988. (in Polish)
- 18. Hasegawa K., Kitera K.: Mathematical Model of Manoeuvrability at Low Advance Speed and its Application to Berthing Control, In: Proceedings of the 2nd Japan-Korea Joint Workshop of Ship and Marine Hydrodynamics, Osaka, Japan, 1993, pp. 144-153.
- 19. Gierusz W.: Simulation model of the shiphandling training boat ”Blue Lady”, In: Proceedings of the 5th IFAC Conference on Control Application in Marine Systems (CAMS-01), 2001, Glasgow, Scotland.
- 20. Skjetne R., Smogeli O., Fossen T.I.: A nonlinear ship maneuvering model: Identification and adaptive control with experiments for a model ship, Modeling, Identification and Control, Vol. 25, No 1, 2004, pp. 3-27.
- 21. Obreja D., Nabergoj R., Crudu L., Pacuraru-Popoiu S.: Identification of hydrodynamic coefficients for manoeuvring simulation model of a fishing vessel, Ocean Engineering, Vol. 37, No 7-8, 2010, pp. 678-687.
- 22. Herrero R.R., Gonzales F.J.V.: Two-step identification of non-linear manoeuvering models of marine vessels, Ocean Engineering, Vol. 53, No 10, 2012, p. 72-82.
- 23. Shouji K., Ohtsu K., Mizoguchi S.: An Automatic Berthing Study by Optimal Control Techniques, In: Proceedings of the IFAC Workshop on Control Application in Marine Systems (CAMS-92), Genova, Italy, 1992, pp. 185-194.
- 24. Ohtsu K., Shouji K.: Minimum-time maneuvering of ships with wind disturbances, Control Engineering Practice, Vol. 4, No 3, 1996, pp. 385-392.
- 25. Okazaki T., Ohtsu K. Shouji K.: A study of minimum time berthing solution, In: Proceedings of the 5th IFAC Conference on Manoeuvring and Control of Marine Craft (MCMC-2000), Aalborg, Denmark, 2000, pp. 135-139.
- 26. Mizuno N., Kuroda M., Okazaki T., Ohtsu K.: Minimum time ship manoeuvring method using neural network and nonlinear model predictive compensator, Control Engineering Practice, Vol. 15, No 6, 2007, pp. 757-765.
- 27. Sarioz K., Narli E.: Assesssment of manoeuvering performance of large tankers in restricted waterways: a real-time simulation approach, Ocean Engineering, Vol. 30, No 12, 2003, pp. 1535-1551.
- 28. Zhang Y., Hearn G.E. Sen P.: A Multivariable Neural Controller for Automatic Ship Berthing, Journal of IEEE Control System, Vol. 17, No 8, 1997, pp. 31-44.
- 29. Im N., Keon L.S., Do B.H.: An application of ANN to automatic ship berthing using selective controller, TransNav – International Journal of Marine Navigation and Safety of Sea Transportation, Vol. 1, No 1, 2007, pp. 101-105.
- 30. Skjetne R., Fossen T.I., Kokotovic P.V.: Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory, Automatica, Vol. 41, No 2, 2005, pp. 289-298.
- 31. Gierusz W., Nguyen Cong V., Rak A., Maneuvering control and trajectory tracking of very large crude carrier, Ocean Engineering, Vol. 34, No 7, 2007, pp. 932-945.
- 32. Morawski L., Nguyen Cong V.: Ship Control in Manoeuvering Situation with Fuzzy Logic Controllers, TransNav – International Journal of Marine Navigation and Safety of Sea Transportation, Vol. 2, No 1, 2008, pp. 77-84.
- 33. Morawski L., Nguyen Cong V.: Problem of Stopping Vesssel at the Waypoint for Full-Mission Control Autopilot, TransNav – International Journal of Marine Navigation and Safety of Sea Transportation, Vol. 4, No 2, 2010, pp. 151-156.
- 34. Lee G., Surendran S., Kim S.-H.: Algorithms to control the moving ship during harbour entry, Applied Mathematical Modelling, Vol. 33, No 5, 2009, pp. 2474-2490.
- 35. Bui V.P., Kawai H., Kim Y.B., Le K.S.: A ship berthing system design with four tug boats, Journal of Mechanical Science and Technology, Vol. 25, No 5, 2011, pp. 1257-1264.
- 36. Tomera M.: Discrete Kalman filter design for multivariable ship motion control: experimental results with training ship, Joint Proceedings of Gdynia Maritime Academy and Hochschule Bremerhaven, Bremerhaven, 2010, pp. 26-34.
- 37. Tomera M.: Kalman-Bucy filter design for multivariable ship motion control, TransNav – International Journal of Marine Navigation and Safety of Sea Transportation, Vol. 5, No 3, 2011, pp. 345-355.
- 38. Tomera M.: Nonlinear observers design for multivariable ship motion control, Polish Maritime Research, Issue Special, Vol. 19, No 74, 2012, pp. 50-56.
- 39. Tomera M.: Dynamic positioning system for „Blue Lady”. Simulation tests, Polish Maritime Research, Issue Special, Vol. 19, No 74, 2012, pp. 57-65.
- 40. Foundation for Safety of Navigation and Environment Research, 2012. <www.ilawashiphandling. com.pl>
- 41. Fossen T.I.: Marine Control Systems: Guidance, Navigation, and Control of Ships, Rigs and Underwater Vehicles, Marine Cybernetics, Trondheim, Norway, 2002.
- 42. Brown R.G., Hwang P.Y.C.: Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions, Third Edition, John Wiley & Sons, Inc, 1997.
- 43. Fossen T.I.: Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons, 2011.
- 44. Pomirski J., Rak, A., Gierusz W.: Control system for trials on material ship model, Polish Maritime Research, Special Isssue, Vol. 19, No 74, 2012, pp. 25-30.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.agro-edf99e0b-00a1-40b6-82c1-419c9ebaac44