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    A novel deep learning backstepping controller-based digital twins technology for pitch angle control of variable speed wind turbine

    , Article Designs ; Volume 4, Issue 2 , 2020 , Pages 1-19 Parvaresh, A ; Abrazeh, S ; Mohseni, S. R ; Zeitouni, M. J ; Gheisarnejad, M ; Khooban, M. H ; Sharif University of Technology
    MDPI AG  2020
    Abstract
    This paper proposes a deep deterministic policy gradient (DDPG) based nonlinear integral backstepping (NIB) in combination with model free control (MFC) for pitch angle control of variable speed wind turbine. In particular, the controller has been presented as a digital twin (DT) concept, which is an increasingly growing method in a variety of applications. In DDPG-NIB-MFC, the pitch angle is considered as the control input that depends on the optimal rotor speed, which is usually derived from effective wind speed. The system stability according to the Lyapunov theory can be achieved by the recursive nature of the backstepping theory and the integral action has been used to compensate for...