Energy Systems

, Volume 10, Issue 1, pp 211–229 | Cite as

Super-twisting sliding mode control approach with its application to wind turbine systems

  • F. Zargham
  • A. H. MazinanEmail author
Original Paper


Wind turbine technologies witness a booming increase in outperforming a set of traditional techniques with respect to state-of-the-art, where Europe plays the vanguard role to highlight the last investigated outcomes. It is to note that turbine systems with longer blades make it possible to extract power from wind, efficiently, accurately and economically. These types of machines are generally able to deal with higher wind velocities by providing their blades to be pitched, due to the fact that the nonlinear nature of the system under control necessitates the realization of nonconventional, efficient and reliable control approaches. In a word, the traditional ones do not have the sufficient merit to maintain the closed loop performance in the presence of disturbances and uncertainties. A possible solution to focus on the above-referenced point is to design the robust nonlinear control technique with rapid response and high accuracy to be free of any perturbation toward uncertainties. Regarding determining effect of the blade pitch control in the output power, the current research aims us to concentrate on delivering an acceptable power to the grid though controlling pitch angles of wing turbine. The novelty behind the research is to investigate the efficient formulation regarding the high-order super-twisting sliding mode blade pitch control approach to ameliorate the effects of linearization and also to reduce the chattering of applied force signal in the wind turbine systems, in order to cope with higher wind velocities through pitch angle accurately. The results investigated in the present research indicate that the states of the system under control can be desirable and the deviations of the control inputs are somehow negligible via the proposed control one that usher to its robust behavior.


Robust nonlinear blade pitch control approach Wind turbine systems Delivering power to the grid High-order super-twisting sliding mode control approach Pitch angle Uncertainties 


\(\theta \)

Rotor pitch angle (\(\circ \))

\({\Delta }\)

Twist of rotor shaft (rad)

\({\Lambda }\)

Tip speed ratio (–)


Air density (kg/m\(^3\))

\(\omega _r \)

Angular speed of rotor (rad/s)

\(\omega _g \)

Angular speed of generator (rad/s)

\(D_g \)

Generator damping (N m s)

\(D_S \)

Shaft damping (N m s)

\(J_g \)

Inertia of generator (kg m\(^2\))

\(J_r \)

Inertia of rotor (kg m\(^2\))

\(K_s \)

Spring constant of shaft (N m)

\(N_g \)

Gear ratio (–)

\(P_e \)

Power generated by generator (W)

\(P_r \)

Mechanical power absorbed from the wind (W)

\(R_r \)

Radius of rotors (m)

\(T_g \)

Generator load torque (N m)

\(T_r \)

Torque transferred from rotor to the gear (N m)

\(T_{sg} \)

Rotor torque transferred to generator (N m)

\(T_{sr} \)

Generator torque transferred to rotor (N m)


Effective wind speed (m/s)

\(V_f \)

Fluctuating wind speed (m/s)

\(V_m \)

Mean wind speed (m/s)

\(C_p \)

Rotor efficiency coefficient (–)


  1. 1.
    Mohammadi, K., Mostafaeipour, A., Sedaghat, A., Shamshirband, S., Petković, D.: Application and economic viability of wind turbine installation in Lutak, Iran. Environ. Earth Sci. 75(3), 1–16 (2016)Google Scholar
  2. 2.
    Phan, D.H., Huang, S.: Super-twisting sliding control design of three-phase inverter for stand-alone distributed generation systems. J. Control Autom. Electr. Syst. 27(2), 179–88 (2016)CrossRefGoogle Scholar
  3. 3.
    Twidell, J., Weir, T.: Renewable Energy Resources. Routledge, New York (2015)CrossRefGoogle Scholar
  4. 4.
    Stiesdal H.: The Bonus 750 KW Wind Turbine, European Union Wind Energy Conference. pp. 215–218 (1996)Google Scholar
  5. 5.
    Díaz-González, F., Sumper, A., Gomis-Bellmunt, O., Villafáfila-Robles, R.: A review of energy storage technologies for wind power applications. Renew. Sustain. Energy Rev. 16(4), 2154–71 (2012)CrossRefGoogle Scholar
  6. 6.
    Wang, B., Qian, Y., Zhang, Y.: Robust nonlinear controller design of wind turbine with doubly fed induction generator by using Hamiltonian energy approach. J. Control Theory Appl. 11(2), 282–87 (2013)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Goudarzi, N., Zhu, W.D.: A review on the development of wind turbine generators across the world. Int. J. Dyn. Control 1(2), 192–202 (2013)CrossRefGoogle Scholar
  8. 8.
    Zhang, P., Huang, S.: Review of aeroelasticity for wind turbine: current status, research focus and future perspectives. Front. Energy 5(4), 419–34 (2011)MathSciNetGoogle Scholar
  9. 9.
    Abdallah, I., Natarajan, A., Sorensen, J.D.: Influence of the control system on wind turbine loads during power production in extreme turbulence: structural reliability. Renew. Energy 87, 464–77 (2016)CrossRefGoogle Scholar
  10. 10.
    Evangelista, C., Valenciaga, F., Puleston, P.: Active and reactive power control for wind turbine based on a mimo 2-sliding mode algorithm with variable gains. IEEE Trans. Energy Convers. 28(3), 682–89 (2013)CrossRefGoogle Scholar
  11. 11.
    Corradini, M.L., Ippoliti, G., Orlando, G.: Robust control of variable-speed wind turbine systems based on an aerodynamic torque observer. IEEE Trans. Control Syst. Technol. 21(4), 1199–206 (2013)CrossRefGoogle Scholar
  12. 12.
    Lin, W.M., Hong, C.M., Ou, T.C., Chiu, T.M.: Hybrid intelligent control of PMSG wind generation system using pitch angle control with RBFN. Energy Convers. Manag. 52(2), 1244–51 (2011)CrossRefGoogle Scholar
  13. 13.
    Jiao, B., Wang, L.: RBF neural network sliding mode control for variable-speed adjustable-pitch system of wind turbine. In: IEEE International Conference on Electrical and Control Engineering (2010)Google Scholar
  14. 14.
    Belabbas, B., Allaoui, T., Tadjine, M., Denai, M.: Power management and control strategies for off-grid hybrid power systems with renewable energies and storage. Energy Syst. (2017) (in press) Google Scholar
  15. 15.
    Falehi, A.D., Rafiee, M.: Fault ride-through capability enhancement of DFIG-based wind turbine using novel dynamic voltage restorer based on two switches boost converter coupled with quinary multi-level inverter. Energy Syst. (2017) (in press) Google Scholar
  16. 16.
    Xu, L., Yang, X., Liu, X., Xu, D.: Based on adaptive fuzzy sliding mode controller. In: 7th IEEE World Congress on Intelligent Control and Automation (2008)Google Scholar
  17. 17.
    Aghatehrani, R., Kavasseri, R.: Sensitivity-analysis-based sliding mode control for voltage regulation in microgrids. IEEE Trans. Sustain. Energy 4(1), 50–57 (2013)CrossRefGoogle Scholar
  18. 18.
    Susperregui, A., Martinez, M.I., Tapia, G., Vechiu, I.: Second-order sliding-mode controller design and tuning for grid synchronization and power control of a wind turbine-driven DFIG. IET Renew. Power Gener. 7(5), 540–51 (2013)CrossRefGoogle Scholar
  19. 19.
    Martinez, M., Susperregui, A., Tapia, G., Xu, L.: Sliding-mode control of a wind turbine-driven double-fed induction generator under non-ideal grid voltages. IET Renew. Power Gener. 7(4), 370–79 (2013)CrossRefGoogle Scholar
  20. 20.
    Hu, J., Nian, H., Hu, B., He, Y., Zhu, Z.Q.: Direct active and reactive power regulation of DFIG using sliding-mode control approach. IEEE Trans. Energy Convers. 25(4), 1028–39 (2010)CrossRefGoogle Scholar
  21. 21.
    Benelghali, S., Benbouzid, M.E.H., Charpentier, J.F., Ahmed-Ali, T., Munteanu, I.: Experimental validation of a marine current turbine simulator: application to a permanent magnet synchronous generator-based system second-order sliding mode control. IEEE Trans. Ind. Electron. 58(1), 118–26 (2011)CrossRefGoogle Scholar
  22. 22.
    Yan, J., Lin, H., Feng, Y., Guo, X., Huang, Y., Zhu, Z.Q.: Improved sliding mode model reference adaptive system speed observer for fuzzy control of direct-drive permanent magnet synchronous generator wind power generation system. IET Renew. Power Gener. 7(1), 28–35 (2013)CrossRefGoogle Scholar
  23. 23.
    Senjyu, T., Sakamoto, R., Urasaki, N., Funabashi, T., Fujita, H., Sekine, H.: Output power leveling of wind turbine generator for all operating regions by pitch angle control. IEEE Trans. Energy Convers. 21(2), 467–75 (2006)CrossRefGoogle Scholar
  24. 24.
    Kim, I.S., Kim, M.B., Youn, M.J.: New maximum power point tracker using sliding-mode observer for estimation of solar array current in the grid-connected photovoltaic system. IEEE Trans. Ind. Electron. 53(4), 1027–35 (2006)CrossRefGoogle Scholar
  25. 25.
    Koutroulis, E., Kalaitzakis, K.: Design of a maximum power tracking system for wind-energy-conversion applications. IEEE Trans. Ind. Electron. 53(2), 486–94 (2006)CrossRefGoogle Scholar
  26. 26.
    Beltran, B., Ahmed-Ali, T., Benbouzid, M.E.H.: Sliding mode power control of variable-speed wind energy conversion systems. IEEE Trans. Energy Convers. 23(2), 551–58 (2008)CrossRefGoogle Scholar
  27. 27.
    De Battista, H., Mantz, R.J., Christiansen, C.F.: Dynamical sliding mode power control of wind driven induction generators. IEEE Trans. Energy Convers. 15(4), 451–57 (2000)CrossRefGoogle Scholar
  28. 28.
    Thomsen, S.C.: Nonlinear control of a wind turbine. Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark (2006)Google Scholar
  29. 29.
    Slootweg, J.G., Polinder, H., Kling, W.L.: Dynamic modeling of a wind turbine with doubly fed induction generator. In: Power Engineering Society Summer Meeting. IEEE (2001)Google Scholar
  30. 30.
    Rivera, J., Raygoza, J.J., Mora, C., Garcia, L., Ortega, S.: Super-Twisting Sliding Mode in Motion Control Systems. INTECH Open Access Publisher, Croatia (2011)Google Scholar
  31. 31.
    Moreno, J.A., Osorio, M.: A Lyapunov approach to second-order sliding mode controllers and observers. In: 47th IEEE Conference on Decision and Control (2008)Google Scholar
  32. 32.
    Levant, A., Alelishvili, L.: Integral high-order sliding modes. IEEE Trans. Autom. Control 52(7), 1278 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  33. 33.
    Levant, A.: Quasi-continuous high-order sliding-mode controllers. IEEE Trans Autom. Control 50(11), 1812–16 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  34. 34.
    Levant, A.: Sliding order and sliding accuracy in sliding mode control. Int. J. Control 58(6), 1247–63 (1993)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Control Engineering, South Tehran BranchIslamic Azad University (IAU)TehranIran
  2. 2.Department of Control Engineering, Faculty of Electrical Engineering, South Tehran BranchIslamic Azad University (IAU)TehranIran

Personalised recommendations