NDLI: Adaptive stator and rotor resistance identification for induction machine without rotational transducer

Content Provider	IEEE Xplore Digital Library
Author	Liu Jingbo Wang Xiuqing
Copyright Year	2008
Description	Author affiliation: Hebei Univ. of Eng., Handan (Liu Jingbo)
Abstract	This paper introduces a new method of stator resistance identification based on wavelet network in order to improve the low-speed dynamic performance of induction motor in direct torque control. Because of the advantage of wavelet transform, the desired feature of the transient signal can be extracted conveniently from both the magnitudes and arguments of wavelet coefficients and the control precision for direct torque control can be increased. The input node of wavelet network is the stator current error and the change in the stator current error. The output node of the wavelet network is the stator resistance error. The wavelet network structure and parameter identification are fulfilled by the evolutionary algorithm. Then in order to optimize the inverter control strategy, the accurate stator flux vector and electromagnetic torque are acquired by means of state estimator. The experiment results show that this new method can efficiently reduce the torque ripple and current ripple and is better than that of the back-propagation neural network.
Starting Page	652
Ending Page	655
File Size	106941
Page Count	4
File Format	PDF
ISBN	9787900719706
DOI	10.1109/CHICC.2008.4605071
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute Of Intelligence M&C Technical Of KMUST
Subject Keyword	Wavelet transforms Resistance Torque Wavelet transformation Torque control Induction machine Artificial neural networks Stators Wavelet analysis Parameter identification Neural network training Direct torque control
Content Type	Text
Resource Type	Article

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