Direct self control of induction motor based on neural network

K. L. Shi, T. F. Chan, Y. K. Wong, Siu Lau Ho

Research output: Journal article publicationJournal articleAcademic researchpeer-review

36 Citations (Scopus)

Abstract

This paper presents an artificial-neural-network-based direct-self-control (ANN-DSC) scheme for an inverter-fed three-phase induction motor. In order to cope with the complex calculations required in direct self control (DSC), the proposed artificial-neural-network (ANN) system employs the individual training strategy with fixed-weight and supervised models. A computer simulation program is developed using Matlab/Simulink together with the Neural Network Toolbox. The simulated results obtained demonstrate the feasibility of ANN-DSC. Compared with the classical digital-signal-processor-based DSC, the proposed ANN-based scheme incurs much shorter execution times and, hence, the errors caused by control time delays are minimized.
Original languageEnglish
Pages (from-to)1290-1298
Number of pages9
JournalIEEE Transactions on Industry Applications
Volume37
Issue number5
DOIs
Publication statusPublished - 1 Sep 2001

Keywords

  • Direct self control
  • Induction motor drive
  • Matlab/Simulink
  • Neural networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Engineering (miscellaneous)

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