• DocumentCode
    2368530
  • Title

    Artificial Neural Network Based Implementation of Space Vector Modulation for Voltage Fed Inverter Induction Motor Drive

  • Author

    Sadati, Nasser ; Barati, Farhad

  • Author_Institution
    Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran
  • fYear
    2006
  • fDate
    6-10 Nov. 2006
  • Firstpage
    4410
  • Lastpage
    4414
  • Abstract
    In this paper, a neural network based implementation of space vector modulation (SVM) of a two-level voltage fed inverter is proposed. This network has the advantage of very fast implementation of SVM algorithm, particularly when a dedicated application-specific IC chip is used instead of a digital signal processor (DSP). The proposed neural network consists of several subnets, a counter and a logic circuit. Subnets are used to implement the stages of SVM algorithm while the counter is used to apply the switching state vectors in their specified times to inverter. The logic circuit generates the inverter switches commands according to the outputs of the subnets. The scheme has been evaluated on an induction motor drive which results in an excellent performance. According to straight forward steps of the artificial neural network (ANN) design, the modulator can be easily extended to multi-level inverters
  • Keywords
    application specific integrated circuits; digital signal processing chips; electric machine analysis computing; induction motor drives; invertors; neural nets; switching convertors; DSP; application-specific IC chip; artificial neural network; digital signal processor; logic circuits; multilevel inverters; space vector modulation; switching state vectors; voltage fed inverter induction motor drive; Application specific integrated circuits; Artificial neural networks; Counting circuits; Digital integrated circuits; Induction motor drives; Inverters; Logic circuits; Signal processing algorithms; Support vector machines; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
  • Conference_Location
    Paris
  • ISSN
    1553-572X
  • Print_ISBN
    1-4244-0390-1
  • Type

    conf

  • DOI
    10.1109/IECON.2006.347311
  • Filename
    4153222