neuro-second order sliding mode control of a dfig supplied by a two-level nsvm inverter for wind turbine system

This paper applied second order sliding mode control (sosmc) strategy using artificial neural network (ann) on the rotor side converter of a 1.5 mw doubly fed induction generator (dfig) integrated in a wind turbine system. in this work, the converter is controlled by a neural space vector modulation (nsvm) technique in order to reduce powers ripples and total harmonic distortion (thd) of stator current. the validity of the proposed control technique applied on the dfig is verified by matlab/simulink. the active power, reactive power, torque and stator current are determined and compared with conventional control method. simulation results presented in this paper shown that the proposed control scheme reduces the thd value and powers ripples compared to traditional control under various operating conditions.