Position sensorless driving of BLDCM using neural networks
Copyright policy ) Hai-Jiao Guo; Seiji Sagawa; Osamu Ichinokura;
Position sensorless driving of BLDCM using neural networks
AbstractA sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(4): 64–71, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20240
- Tohoku Gakuin University Japan
- Tohoku University Japan
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selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 8
Top 10%
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