NDLI: Sensorless vector control of induction motor using artificial neural network

Content Provider	IEEE Xplore Digital Library
Author	Hung-Ching Lu Ta-Hsiung Hung Cheng-Hung Tsai
Copyright Year	2000
Description	Author affiliation: Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan (Hung-Ching Lu)
Abstract	This paper presents a novel approach to sensorless vector control of induction motor drives. The method is based on an adaptive flux observer in the rotor-speed reference frame, in which an artificial neural network (ANN) is employed to modify the estimated rotor flux to improve the performance of speed estimation. The adopted ANN is a feedforward neural network identified off-line. It uses the backpropagation learning process to update the weights. The data for training are obtained from a computer simulation and experimental data file of a vector control system. Then, the estimated rotor flux is used in the speed estimation that will feed back to the vector control system, The proposed method has the advantages of better accuracy at low speed range and speed following under heavy loads. The whole system is implemented in a TMS320C30 DSP chip and experimental results show the effectiveness of the proposed method.
Starting Page	489
Ending Page	492
File Size	316280
Page Count	4
File Format	PDF
ISBN	0780354826
DOI	10.1109/ISCAS.2000.856372
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-05-28
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Machine vector control Induction motors Artificial neural networks Rotors Induction motor drives Neural networks Feedforward neural networks Backpropagation Computer simulation Feeds
Content Type	Text
Resource Type	Article

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