On-Line Instant Torque Estimation of Switched Reluctance Motor Using Adaptive B-spline Neural Network

Zhengyu Lin, Donald Shewan Reay, Barry Wayne Williams, Xiang Ning He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A novel on-line instant torque estimation scheme for a switched reluctance motor (SRM) is presented. In the proposed method, an adaptive B-spline neural network is used to learn the non-linear flux-linkage and torque characteristics of a SRM. Due to the local nature of its generalisation properties, the training of the B-spline neural network is accomplished on-line and in real-time, and the system does not require a priori knowledge of the machine's electromagnetic characteristics. The potential of the method is demonstrated successfully in simulation and experimentally using a 300W 12/8 3-phase SRM.

Original languageEnglish
Title of host publicationProceedings of the 29th Annual Conference of the IEEE Industrial Electronics Society, 2003
Pages1033-1037
Number of pages5
Volume2
DOIs
Publication statusPublished - 2003
Event29th Annual Conference of the IEEE Industrial Electronics Society - Roanoke, VA, United States
Duration: 2 Nov 20036 Nov 2003

Conference

Conference29th Annual Conference of the IEEE Industrial Electronics Society
CountryUnited States
CityRoanoke, VA
Period2/11/036/11/03

Keywords

  • Neural network
  • Switched reluctance motors
  • Torque estimation

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