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Mathematical Problems in Engineering
Volume 2014, Article ID 831839, 10 pages
Research Article

Rotor Resistance Online Identification of Vector Controlled Induction Motor Based on Neural Network

1Information Engineering College, Henan University of Science and Technology, Luoyang 471023, China
2Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macau
3Faculty of Business Administration, University of Macau, Macau

Received 7 May 2014; Accepted 3 August 2014; Published 25 September 2014

Academic Editor: Chengjin Zhang

Copyright © 2014 Bo Fan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Rotor resistance identification has been well recognized as one of the most critical factors affecting the theoretical study and applications of AC motor’s control for high performance variable frequency speed adjustment. This paper proposes a novel model for rotor resistance parameters identification based on Elman neural networks. Elman recurrent neural network is capable of performing nonlinear function approximation and possesses the ability of time-variable characteristic adaptation. Those influencing factors of specified parameter are analyzed, respectively, and various work states are covered to ensure the completeness of the training samples. Through signal preprocessing on samples and training dataset, different input parameters identifications with one network are compared and analyzed. The trained Elman neural network, applied in the identification model, is able to efficiently predict the rotor resistance in high accuracy. The simulation and experimental results show that the proposed method owns extensive adaptability and performs very well in its application to vector controlled induction motor. This identification method is able to enhance the performance of induction motor’s variable-frequency speed regulation.