Abstract
This paper presents an ANN-based (artificial neural network-based) method of stator resistance tuning in an IRFO (indirect rotor field oriented) control system of an induction motor. This method is based on the conventional two-layer ANN in which the rotor time constant is not a constant parameter and is identified using a model reference adaptive system (MRAS) - based procedure. During the training, rotor speed estimation of the induction motor is enabled. The difference between the actual and the estimated rotor speed is used as a signal for manual stator resistance tuning. Computer simulations and experimental results show the effectiveness of the described approach in a low rotor speed region.
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Vukadinovic, D., Basic, M., Kulisic, L. (2008). Stator Resistance Tuning Based on a Neural Network in an Indirect Rotor Field Oriented Control System of an Induction Motor. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85563-7_83
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DOI: https://doi.org/10.1007/978-3-540-85563-7_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85562-0
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