Discrete-time neural block control for a doubly fed induction generator

This paper proposes a control scheme based on the discrete-time block control technique using sliding modes, for a doubly fed induction generator connected to an infinity bus. In order to obtain the generator mathematical model, it is proposed to use a recurrent high order neural network (RHONN) identifier, which is trained with an extended Kalman filter (EFK) algorithm. Parameter changes are applied to test the scheme robustness. Its performance is illustrated via simulations.