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Adaptive sliding mode control for ship autopilot with speed keeping

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper addresses an important issue in surface vessel motion control practice that the ship dynamics and sailing performance can be affected by speed loss. The vessel speed is significantly decreased by the added resistance generated by waves. An adaptive sliding mode course keeping control design is proposed which takes into account uncertain ship dynamics caused by forward speed variations, while avoiding performance compromises under changing operating and environmental conditions. The sliding mode control provides robust performance for time-varying wave disturbances and time-varying changes in ship parameters and actuator dynamics. After combining the unknown but bounded system uncertainties, the design of the adaptation law is obtained which is based on the Lyapunov’s direct method. Simulations on a ship with two rudders illustrate the effectiveness of the proposed solution.
Rocznik
Tom
Strony
21--29
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Shanghai Maritime University, Shanghai, China
Bibliografia
  • 1. Fossen T.I.: Handbook of marine craft hydrodynamics and motion control. Wiley, West Sussex, 2011.
  • 2. Do K.D., Jiang Z.P., Pan J.: Robust adaptive path following of underactuated ships. Automatica, vol. 40, no. 6, 929, 2004.
  • 3. Zhang G., Zhang X., Zheng Y.: Adaptive neural path following control for underactuated ships in fields of marine practice. Ocean Engineering, no. 104, 558, 2015.
  • 4. Shojaei K.: Neural adaptive robust control of underactuated marine surface vehicles with input saturation. Applied Ocean Research, no. 53, 267, 2015.
  • 5. Li J.H., Lee P.M., Jun B.H., Lim Y.K.: Point to point navigation of underactuated ships. Automatica, vol. 44, no. 12, 3201, 2008.
  • 6. Peng Z., Wang D., Chen Z., Hu X., Lan W.: Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics. IEEE Transactions on Control System Technology, vol.21, no. 2, 513, 2013.
  • 7. Do K.D., Pan J., Jiang Z.P.: Robust adaptive control of underactuated ships on a linear course with comfort. Ocean Engineering, vol. 30, no. 7, 2201, 2003.
  • 8. Li H., Liu J., Hilton C., Liu H.: Adaptive sliding mode control for nonlinear active suspension vehicle systems using T-S fuzzy approach. IEEE Transactions on Industrial Electronics, vol. 60, no. 8, 3328, 2013.
  • 9. Kahveci N., Ioannou P.A.: Adaptive steering control for uncertain ship dynamics and stability analysis. Automatica, vol. 49, no. 3, 685, 2013.
  • 10. Lin C., Hsuen C., Chen C.: Robust adaptive backstepping control for a class of nonlinear systems using recurrent wavelet neural network [J]. Neurocomputing, no. 142, 372, 2014.
  • 11. Cristi R., Papoulias F.A., Healey A.J.: Adaptive sliding mode control of autonomous underwater vehicles in the dive plane. IEEE Journal of Oceanic Engineering, vol. 15, no. 3, 152, 1990.
  • 12. Do K.D., Pan J., Jiang Z.P.: Robust and adaptive path following for underactuated autonomous underwater vehicles. Ocean Engineering, vol. 31, no. 6, 1967, 2004.
  • 13. Liu Y., Liu S., Wang N.: Fully tuned fuzzy neural network robust adaptive tracking control of unmanned under water vehicle with thruster dynamics. Neurocomputing, no. 196, 1, 2016.
  • 14. Prpic-Orsic J., Faltinsen O.M.: Estimation of ship speed loss and associated CO2 emissions in a sea way. Ocean Engineering, vol. 44, no. 1, 1, 2012.
  • 15. Arribas F.P.: Some methods to obtain the added resistance of a ship advancing in waves. Ocean Engineering, vol. 34, no. 7, 946, 2007.
  • 16. Armstrong V.N.: Vessel optimisation for low carbon shipping. Ocean Engineering, no. 73, 195, 2013.
  • 17. Liu Z., Jin H.: Extended radiated energy method and its application to a ship roll stabilisation control system. Ocean Engineering, vol. 72, no. 7, 25, 2013.
  • 18. Faltinsen O.M.: Hydrodynamics of High Speed Vehicles. Cambridge University Press, Cambridge 2005.
  • 19. Akinsal V.: Surface ship fuel saving with an optimized autopilot, master dissertation. Naval Postgraduate School, Monterey, 1985.
  • 20. Grimble M.J., Katabi M.R.: LQG design of ship steering control systems. Signal Processing for Control, Lecture Notes in Control and Information Sciences, no. 79, 387, 1986.
  • 21. Miloh T., Pachter M.: Ship collision-avoidance and pursuitevasion differential games with speed-loss in a turn. Computers Mathematics with Application, vol. 18, no. 1, 77, 1989.
  • 22. Kim S.S., Kim S.D., Kang D., Lee J., Lee S.J., Jung K.H.: Study on variation in ship’s forward speed under regular waves depending on rudder controller. International Journal of Naval Architecture and Ocean Engineering, vol. 7, no. 2, 364, 2015.
  • 23. Liu Z., Jin H., Grimble M.J., Katebi R.: Ship forward speed loss minimization using nonlinear course keeping and roll motion controllers. Ocean Engineering, no. 113, 201, 2016.
  • 24. Perez T.: Ship Motion Control: Course Keeping and Roll Reduction Using Rudder and Fins. Springer, London, 2005.
  • 25. Loukakis T.A., Sclavounos P.: Some extensions of the classical approach to strip theory of ship motion including the calculation of mean added forces and moments. Journal of Ship Research, vol. 22, no. 1, 1, 1978.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9b509df2-0ebf-4636-accf-42bb18635cb9
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