A neuro-fuzzy approach for stator resistance estimation of induction motor
An accurate estimation of stator resistance is very important especially during operation of an induction motor due to variation in the stator resistance and temperature of the working machine. This paper proposes a Neuro-fuzzy Technique (NFT) for an online estimation of the stator resistance under steady state operating conditions of an induction motor. The proposed technique is compared with the Proportional Integral (PI) estimator to see the effectiveness. The obtained results of applying the NFT for resistance estimation give better performance and high robustness than those obtained by the application of PI.