1. An adaptive pitch control system for a wind generator, the wind generator being a doubly fed induction generator (DFIG) having blade pitch servos for adjusting blade pitch of the DFIG wind generator, the system comprising: means for determining a theoretically maximum reference power of the wind generator based on rotor speed and a plurality of given pitch angles; a proportional-integral (PI) pitch controller having an input, a proportional gain constant K P , an integral gain constant K I , and an output adapted for connection to the blade pitch servos, the PI pitch controller output including means for sending pitch angle commands β to the blade pitch servos to control pitch angle of the blades; a back propagation neural network (BPNN) having a plurality of signal paths and a corresponding plurality of weights applied to said plurality of signal paths, said back propagation neural network being in communication with said PI controller; means for feeding back system states of the wind generator to said PI pitch controller; means for tuning said plurality of weights based on said feedback of said system states, wherein said means for tuning said plurality of weights comprises means for generating a training dataset applied to said BPNN; means for determining actual power output of the wind generator; means for determining the difference between the actual power output of the wind generator and the theoretically maximum reference power, the difference resulting in an error power signal; means for applying said error power signal to the PI pitch controller input; means for additively combining the K p multiplied by the error power signal with the K I multiplied by a time integral of the error power signal, the additive combination means forming the PT pitch controller output of the pitch angle commands β; means for adaptively adjusting the K p and the K I based on the error power signal; means for generating a random number having values of said wind speeds between a first predetermined wind speed and a second predetermined wind speed to define a randomly generated wind speed; means for saving the randomly generated wind speed in an input vector; means for picking a wind speed from the input vector; means for generating said K p and said K I for the input vector wind speed; means for saving said K p and said K I in an output vector; and means for collecting a predetermined number of values in the input vector and the output vector, the input vector and the output vector forming said neural network training dataset used to train said back propagation neural network.