Higher Control Scheme Using Neural Second Order Sliding Mode and ANFIS-SVM strategy for a DFIG-Based Wind Turbine

In this paper, we propose an advanced control scheme using neural second order sliding mode (NSOSMC) and adaptive neuro-fuzzy inference system space vector modulation (ANFIS-SVM) strategy for a doubly fed induction generator (DFIG) integrated into a wind turbine system (WTS). The used hybrid control system composed of artificial intelligence techniques and second-order sliding mode applied to ensure better powers performances provided by the WTS. The obtained simulation results showed that the proposed control structure has active and reactive powers with low ripples and low stator current harmonic distortion.