• DocumentCode
    184421
  • Title

    Subspace Predictive Repetitive Control for wind turbine load alleviation using trailing edge flaps

  • Author

    Navalkar, S.T. ; van Wingerden, J.W. ; van Solingen, Edwin ; Oomen, Tom ; van Kuik, G.A.M.

  • Author_Institution
    Delft Center for Syst. & Control, Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    4422
  • Lastpage
    4427
  • Abstract
    A novel Subspace Predictive Repetitive Control (SPRC) methodology is presented and used to control trailing edge flaps for wind turbines. First, the dynamics of the wind turbine are identified online. This is especially important for trailing edge flaps on a large wind turbine, where a local change in wind conditions can result in significantly altered aerodynamics. Next, a repetitive control (RC) law is formulated for the multivariable problem from the identified dynamics, that guarantees stability when the identification converges to the true system parameters. This is done in a lower-dimensional basis-function subspace, which reduces computations and gives high control over the shape of the actuator signal. The SPRC methodology is validated in a high-fidelity wind turbine simulation environment.
  • Keywords
    aerodynamics; multivariable control systems; predictive control; stability; wind; wind turbines; RC law; SPRC methodology; aerodynamics; high-fidelity wind turbine simulation environment; identification; lower-dimensional basis-function subspace; multivariable problem; repetitive control law; stability; subspace predictive repetitive control; trailing edge flaps; wind conditions; wind turbine dynamics; wind turbine load alleviation; Blades; Load modeling; Loading; Rotors; Vectors; Wind speed; Wind turbines; Aerospace; Direct adaptive control; Iterative learning control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6859094
  • Filename
    6859094