A new control method for a grid-connected doubly fed induction generator (DFIG) is proposed in this paper, which is robust against parametric uncertainty and measurement noise. In general, the DFIG controllers can be divided into two main groups: the rotor side converter (RSC) and the grid side converter (GSC) controllers. The parameters of a DFIG may deviate from their rated values due to the operating conditions. For this parametric uncertainty, a robust H∞ vector control (VC) is employed using the complex sensitivity approach. The design of the RSC controller has been carried out using the vector control strategy, and instead of proportional-integral (PI) controllers, a designed robust controller is used. One of the steps in vector control is the extraction of the measured currents to be used in the control equations. If the currents are polluted with noise, the system control will be impaired. Thus, using a Kalman filter is suggested to solve this problem. The effectiveness of the proposed method is then investigated using extensive simulations under various conditions. The obtained results confirm the efficient performance and robustness of the presented controller with model and measurement uncertainties.