This study explores an advanced Sliding Mode Order-One Controller with Artificial Neural Network (ANN) for wind turbine chain equipped with a Doubly Fed Induction Generator (DFIG). The control algorithm incorporates an optimization process, such as PSO, to determine optimal gain parameters. The DFIG is connected directly to the grid in the stator and is fed in the rotor by the Converter Side Rotor (CSR). The initial section of the paper presents the model of the wind turbine system, covering both the mechanical and electrical aspects. The subsequent section introduces a robust control strategy to regulate the active and reactive powers (stator powers) of the DFIG. The proposed control method combines Sliding Mode Order-One (SMOO) with Artificial Neural Network control, aiming to reduce the chattering effect and enhance quality of grid compared to conventional SMOO. This approach, referred to as ANN-SMOO, exhibits improved performance and robustness in DFIG control by mitigating chattering effects and improving energy quality. The paper concludes with the presentation and discussion of simulation results for the entire system.