In this paper, we present the doubly-fed induction generator (DFIG) control in wind energy conversion system using adaptive neuro-fuzzy approach. The wind turbine driven by doubly-fed induction machine is a part of distributed generation which feeds ac power to the distribution network. The system is modeled and simulated in the Matlab Simulink environment in such a way that it can be suited for modeling of all types of induction generator configurations. The model makes use of rotor reference frame using dynamic vector approach for machine model. Adaptive neuro-fuzzy controller is applied to rotor side converter for active power control and voltage regulation of wind turbine. Wind turbine and its control unit are described in details. All power system components and the adaptive neuro-fuzzy controller are simulated in Matlab Simulink software. For studying the performance of controller, different abnormal conditions are applied even the worst case. Simulation results prove the excellent performance of adaptive neuro-fuzzy control unit as improving power quality and stability of wind turbine.