Abstract
This paper proposes a novel control scheme for rotor time constant identification using artificial neural networks. This approach, based on estimation of the rotor time constant from motor terminal variables (stator voltage, stator current and rotor speed), can be applied to indirect field oriented control and used to tune the actual rotor time constant of the induction motor to its set value programmed in the decoupling controller. The neural estimators use the back-propagation learning process to update their weights. The performance of the proposed scheme is carried out by extensive simulations confirming the feasibility of the proposed control strategy.
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Douiri, M.R., Cherkaoui, M. (2013). Intelligent Rotor Time Constant Identification Approach in Indirect Field Oriented Induction Motor Drive. In: Castro, F., Gelbukh, A., González, M. (eds) Advances in Soft Computing and Its Applications. MICAI 2013. Lecture Notes in Computer Science(), vol 8266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45111-9_14
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DOI: https://doi.org/10.1007/978-3-642-45111-9_14
Publisher Name: Springer, Berlin, Heidelberg
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