Intelligent adaptive control of doubly fed induction generator

Induction generators have gained an important rule in many applications. These generators have a very wide rotor speed operation range and reactive power with non-linear characteristics. As a result the linear controllers which have been designed for an operating point don´t show a properly function for controlling the generator outputs. In this paper in order to overcome this problem an adaptive neural controller has been used to control the speed of rotor and the reactive power of the induction generator. The proposed adaptive neural controller is based on the well-known gain scheduling methods where the PI controller parameters have been obtained using genetic algorithm in each operating point. The simulation results show the ability of the proposed controller system in a wide range of applications in comparison to the classical systems.