In order to alleviate fatigue loads for wind turbines due to wind speed disturbances, this paper presents a sliding individual pitch control strategy based on RBF neural network. By analyzing the basic characteristics of the wind turbine, it proposes a control mode combining with RBF neural network sliding mode power control unit and individual pitch control unit. RBF neural network sliding mode power control unit balances the wind rotor via a pneumatic torque control of the generator electromagnetic torque and blade pitch angle, and keeps the amount of speed to achieve the purpose of stable output power wind turbines. RBF neural sliding network individual pitch control unit optimizes unified unit angle signal of power control through fine-tune real pitch angle, and achieves the purpose of relieving structure fatigue loads for wind turbine. Finally, corresponding simulation and experiments based on RBF neural network independent sliding pitch controlled wind turbines are established, it verifies that the proposed method has good control effect, achieves stability output power for large wind turbine, greatly eases structural loads , and reduces the maintenance costs of wind turbines.