Pitch angle control of DFIG using self tuning neuro fuzzy controller

Extracting maximum power and maintaining constant frequency at variable wind speed is the most demanding objective of wind energy system. Various classical control methodologies have been applied to achieve this objective. Due to the unpredictable nature of the wind speed, power varies during controller transition from one region to another. Adaptive neuro-fuzzy controllers are able to control complex non-linear process where the disturbances have a major impact on the control performance. In this paper a self-learning neuro-fuzzy control strategy based on feedback error learning is proposed. The objective is to control the pitch angle in various operating conditions by tuning the controller parameters online. Results are included which demonstrates the efficiency of the self-learning neuro-fuzzy controller in maintaining constant power in variable wind speed.