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Model Predictive Super-Twisting Sliding Mode Control for An Autonomous Surface Vehicle

Abstract

This paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been known as an effective approach for the implementation simplicity and its fast dynamic response. The proposed hybrid controller has been implemented in MATLAB / Simulink environment. The results for the combined Model Predictive Super-Twisting Sliding Mode Control (MP-STSMC) algorithm have shown that it significantly outperforms conventional MPC algorithm in terms of the transient response, robustness and steady state response and presents an effective chattering attenuation in comparison with the Super-Twisting Sliding Mode Control (STSMC) algorithm.

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
Polish Maritime Research no. 26, pages 163 - 171,
ISSN: 1233-2585
Language:
English
Publication year:
2019
Bibliographic description:
Nejatbakhsh Esfahani H., Szłapczyński R.: Model Predictive Super-Twisting Sliding Mode Control for An Autonomous Surface Vehicle// Polish Maritime Research -Vol. 26,iss. 3 (2019), s.163-171
DOI:
Digital Object Identifier (open in new tab) 10.2478/pomr-2019-0057
Bibliography: test
  1. Esfahani, H. N., Azimirad. V., Eslami. A., Asadi. S.): An optimal sliding mode control based on immune-wavelet algorithm for underwater robotic manipulator. Proceedings of the 21st Iranian Conference on Electrical Engineering (ICEE), Mashhad, Iran, 2013. open in new tab
  2. Esfahani, H. N., Azimirad, V., Danesh, M.: A time delay controller included terminal sliding mode and fuzzy gain tuning for underwater vehicle-manipulator systems. Ocean Engineering, Vol. 107, (2015) pp. 97-107.
  3. Esfahani, H. N., Azimirad, V., Zakeri, M.: Sliding Mode-PID Fuzzy controller with a new reaching mode for underwater robotic manipulators. Latin American Applied Research, vol. 44(3), (2014), pp. 253-258.
  4. Liu C., Zheng H., Negenborn R.R., Chu X., Wang L.: Trajectory tracking control for underactuated surface vessels based on nonlinear Model Predictive Control. In: Corman F., Voß S., Negenborn R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science, vol 9335, (2015), pp. 166-180. Springer, Cham. (Proceedings of the 6th International Conference, ICCL 2015, Delft, The Netherlands). open in new tab
  5. Liu, J., Luo, J., Cui, J., Peng, Y.: Trajectory Tracking Control of Underactuated USV with Model Perturbation and External Interference. Procedings of the 3rd International Conference on Mechanics and Mechatronics Research (ICMMR 2016). Chongqing, China , 2016. DOI: 10.1051/ matecconf/20167709009. open in new tab
  6. Wang, W., Mateos, L.A., Park, S., Leoni, P., Gheneti, B., Duarte, F., Ratti, C., Rus, D.: Design , Modeling , and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 6189-6196. Brisbane, Australia, 2018. DOI: 10.1109/ICRA.2018.8460632. open in new tab
  7. Zheng, H., Negenborn, R.R., Lodewijks, G.: Trajectory tracking of autonomous vessels using model predictive control. IFAC Proceedings Volumes. vol. 19, (2014) no. 3, pp. 8812-8818. (Procedings of the 19th IFAC World Congress, Cape Town, South Africa, August 24-29). DOI: 10.3182/20140824-6-ZA-1003.00767. open in new tab
  8. Abdelaal, M., Fr, M., Hahn, A.: Nonlinear Model Predictive Control for trajectory tracking and collision avoidance of underactuated vessels with disturbances. Ocean Eng., Vol. 160, (2018), pp. 168-180. open in new tab
  9. Yi, B., Qiao, L., Zhang, W.: Two-time scale path following of underactuated marine surface vessels : Design and stability analysis using singular perturbation methods. Ocean Eng., Vol. 124, (2016) , pp. 287-297. open in new tab
  10. Valenciaga, F.: A second order sliding mode path following control for autonomous surface vessels. Asian Journal Control, vol. 16(5), (2014), pp. 1515-1521. open in new tab
  11. Tanakitkorn, K., Phillips, A.B., Wilson, P.A., Turnock, S.R. : Sliding mode heading control of an overactuated hover- capable autonomous underwater vehicle with experimental verification. Journal of Field Robotics, vol. 35(3), (2017), pp. 396-415. open in new tab
  12. Hung, N.T., Rego, F., Crasta, N., Pascoal, A.M.: Input- Constrained Path Following for Autonomous Marine Vehicles with a Global Region of Attraction. IFAC-PapersOnLine, vol. 51(29), pp. 348-353. (Proceedings of the 11th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles, CAMS-2018. Opatija, Croatia, 2018. open in new tab
  13. Jamalzade, M.S., Koofigar, H.R., Ataei, M.: Adaptive fuzzy control for a class of constrained nonlinear systems with application to a surface vessel. Journal of Theoretical and Applied Mechanics, vol. 54(3), (2016), pp. 987-1000. open in new tab
  14. Fossen, T.I.: Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons, Ltd., 2011. open in new tab
  15. Fu, M., Yu, L.: Finite-time extended state observer-based distributed formation control for marine surface vehicles with input saturation and disturbances. Ocean Eng., Vol. 159, (2018) , pp. 219-227. open in new tab
  16. Incremona, G. P., Ferrara, A., Magni, L.: Hierarchical Model Predictive/Sliding Mode Control of Nonlinear Constrained Uncertain Systems. IFAC-PapersOnLine, vol. 48(23), (2015) , pp. 102-109. (Proceedings of the 5th IFAC Conference on Nonlinear Model Predictive Control, NMPC-15. Seville, Spain). open in new tab
  17. Esfahani, H. N: Robust Model Predictive Control for Autonomous Underwater Vehicle-Manipulator System with Fuzzy Compensator. Polish Maritime Research (forthcoming), 2019. 10.2478/pomr-2019-00139. open in new tab
  18. Witkowska, A, Smierzchalski, R.: Adaptive dynamic control allocation for dynamic positioning of marine vessel based on backstepping method and sequential quadratic programming. Ocean Engineering, Vol. 163, (2018) , pp. 570-582. open in new tab
  19. Witkowska, A, Smierzchalski, R.: Adaptive Backstepping Tracking Control for an over-Actuated DP Marine Vessel with Inertia Uncertainties. International Journal of Applied Mathematics and Computer Science , Vol. 28(4), (2018), pp. 679-693. open in new tab
  20. Lisowski, J.: Analysis of Methods of Determining the Safe Ship Trajectory. TRANSNAV-International Journal On Marine Navigation And Safety Of Sea Transportation, Vol. 10(2), (2016) , pp. 223-228. open in new tab
  21. Lisowski, J.: Optimization-supported decision-making in the marine mechatronics systems. Solid State Phenomena, vol. 210, (2014), pp. 215-222. open in new tab
  22. Tomera, M.: Ant colony optimization algorithm applied to ship steering control. Procedia Computer Science, vol. 35, (2014) , pp. 83-92. (Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems, 18th Annual Conference, KES-2014. Gdynia, Poland). open in new tab
  23. Fang, Y.: Global output feedback control of dynamically positioned surface vessels : an adaptive control approach. Mechatronics, Vol. 14, (2004) , pp. 341-356. DOI: 10.1016/ S0957-4158(03)00064-3. open in new tab
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Gdańsk University of Technology

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