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Rotor resistance identification using artificial neural networks for an indirect vector controlled induction motor drive

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3 Author(s)
Karanayil, B. ; Sch. of Electr. Eng. & Telecommun., New South Wales Univ., Sydney, NSW, Australia ; Rahman, M.F. ; Grantham, C.

This paper presents a new method of estimation for the rotor resistance of the induction motor in the indirect vector controlled drive. The back propagation neural network technique is used for the real time adaptive estimation. The error between the desired state variable of an induction motor and the actual state variable of a neural model is back propagated to adjust the weights of the neural model, so that the actual state variable tracks the desired value. The performance of the neural estimator and torque and flux responses of the drive, together with this estimator, are investigated with simulations for variations in the rotor resistance from their nominal values

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Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE  (Volume:2 )

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