Speed sensorless control with neuron MRAS estimator of an induction machine

Dong Lei*, Yang Dong, Liao Xiaozhong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In the high speed range, vector control of rotor flux orientation of an induction machine implements good performance. However, the performance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MRAS) for speed estimation are used to improve the performance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved performance in low speed range.

Original languageEnglish
Title of host publication7th International Conference on Power Electronics and Drive Systems, PEDS 2007
Pages1151-1156
Number of pages6
DOIs
Publication statusPublished - 2007
Event7th International Conference on Power Electronics and Drive Systems, PEDS 2007 - Bangkok, Thailand
Duration: 27 Nov 200730 Nov 2007

Publication series

NameProceedings of the International Conference on Power Electronics and Drive Systems

Conference

Conference7th International Conference on Power Electronics and Drive Systems, PEDS 2007
Country/TerritoryThailand
CityBangkok
Period27/11/0730/11/07

Keywords

  • Induction machine
  • MRAS
  • Neuron model
  • Speed sensorless control
  • Stator resistance identification

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