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This article presents a multiple adaptive neuro-fuzzy inference system-based control scheme for operation of the wind energy conversion system above the rated wind speed. By controlling the pitch angle and generator torque concurrently, the generator power and speed fluctuation can be reduced and also turbine blade stress can be minimized. The proposed neuro-fuzzy-based adaptive controller is composed of both the Takagi–Sugeno fuzzy inference system and neural network. First, a step change in wind speed and then a simulated wind speed are considered in the proposed adaptive control design. A MATLAB/Simulink model of the wind turbine system is prepared, and simulations are carried out by applying the proportional integral, fuzzy-proportional integral and the proposed adaptive controller. From the obtained results, the effectiveness of the proposed adaptive controller approach is confirmed.

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