Position sensorless driving of BLDCM using neural networks

Hai Jiao Guo, Seiji Sagawa, Osamu Ichinokura

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


A 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.

Original languageEnglish
Pages (from-to)64-71
Number of pages8
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Issue number4
Publication statusPublished - 2008 Mar 1


  • Brushless DC motor
  • Neural network
  • Position sensorless
  • Vector control

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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