The variable speed wind turbine generator exhibits serious nonlinearity, uncertainty and difficulty accurate modeling, conventional PID controller can't achieve ideal control effect. In this paper, an adaptive inverse control scheme based on neural network identification technology is proposed to solve the above problem. The scheme firstly uses online identification of one DRNN to obtain the Jacobian information of plant. On this basis, another DRNN identifies the inverse plant model which constitutes adaptive inverse control system as controller. The simulation results verify that the adaptive inverse control scheme has excellent adaptability and robustness, which can make the actual rotational speed of wind turbine rapidly track the set point to maintain the best tip-speed ratio in order to get maximum wind energy capture in the random wind conditions.
