A novel position sensorless driving system of brushless DC motors based on neural networks

Hai Jiao Guo, Seiji Sagawa, Tadaaki Watanabe, Osamu Ichinokura

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

In this paper, a position sensorless driving method of brushless DC motors (BLDCMs) using neural networks has been proposed. Considering the nonlinear characteristics of BLDCM and the parameter errors in the modeling, neural networks can be considered as a powerful tool. Thus, we introduce a neural network to estimate the electromotive force (EMF). Instead of directly estimating the position information from EMF, we propose a new method to estimating the position errors and then using approximate algorithm to obtain the rotor position. The results of simulation and experiment using offline trained neural networks show that the BLDCM is controlled well under load conditions. The proposed method can be believed have high possibility in practical applications.

Original languageEnglish
Pages2063-2067
Number of pages5
Publication statusPublished - 2002 Dec 1
EventProceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society - Sevilla, Spain
Duration: 2002 Nov 52002 Nov 8

Other

OtherProceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society
CountrySpain
CitySevilla
Period02/11/502/11/8

Keywords

  • Brushless DC motor
  • Neural networks
  • Position sensorless driving

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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