This paper presents a detailed description of the control algorithm for a wind turbine with a doubly fed induction generator (DFIG). The aerodynamic properties of the wind turbine are estimated using a nonlinear input-output mapping approach, namely a Gaussian radial basis function network. The wind speed is estimated using a nonlinear mapping, which considers the measured generator electrical output power, as well as the power losses in the wind turbine generator (WTG) and the dynamics of the WTG shaft system. The novel control methodology entails the development and comprehensive evaluation of the fuzzy logic controller. Ultimately, the method described in this study is implemented in the wind generation system. Subsequently, the estimated wind speed is employed to ascertain the most favorable command for the DFIG rotor speed, with the objective of maximizing the extraction of wind power. The speed controller of the Doubly Fed Induction Generator (DFIG) is appropriately engineered to efficiently mitigate the effects of low-frequency torsional oscillations. The WTG system achieves optimal electrical power output to the grid, exhibiting superior efficiency and dependability, all while eliminating the need for mechanical anemometers.