The wind system based on double-fed induction generator (DFIG) has become a very important source of energy. To ensure the proper functioning of this system, many improved control algorithms have been developed for the rotor side converter (RSC). This article presents the analysis and design of a double-fed induction generator (DFIG) control technique based on coupling the type-2 fuzzy logic control with the sliding mode control (SMC). For the design of this technique, a decoupled modeling of the DFIG with the orientation of its stator flow is presented. The main purpose of the proposed technique is to make a control to meter the quantities of the powers produced by DFIG which are injected into the electrical network and to reduce the phenomenon of chattering which depends on control by sliding mode. This command has allowed us to reduce the chattering phenomenon and improve the performance of the system in terms of speed monitoring and stator side powers regulation. Simulations are performed using MATLAB / Simulink to validate the effectiveness of the proposed control algorithm. The simulation results, obtained when applying this control strategy to the system, demonstrated the validity of the results and thus validated the high performance of this control technique.

This paper presents a comparative study between two algorithms for controlling the Wind Turbine (WT) using real time platforms: RT-Lab. The Maximum Power Point Tracking (MPPT) control technique is implemented for extracting the maximum energy from the wind. The first control consists in taking as a reference strategy the electromagnetic torque associated with the maximum power curve. This controller is known as Indirect Speed Control (ISC). The second one, based on the measured wind speed, is called Direct Speed Control (DSC). In this second controller, the effectiveness of the controllers was evaluated with a PI controller and a Fuzzy Logic (FL) controller. The performances are analyzed and compared on the OPAL-RT digital simulator, which is based on the RT-LAB platform with the model, and its control built in Simulink. The results of the simulations clearly show that algorithm based on fuzzy controllers gives better performance in terms of monitoring the maximum power coefficient and optimal speed compared to conventional algorithms.