• DocumentCode
    1622540
  • Title

    Modelling of induction motor using non-linear neural network system identification

  • Author

    Mohamed, Faisal A. ; Koivo, Heikki

  • Author_Institution
    Control Eng. Lab., Helsinki Univ. of Technol., Finland
  • Volume
    2
  • fYear
    2004
  • Firstpage
    977
  • Abstract
    This paper is concerned with the black box modelling of induction motor from test data. Data is obtained using a computer-based data acquisition card, the aim of the work described in this paper is to obtain model of the induction motor directly from test data. A pseudo random binary sequence (PRBS) was chosen as the test input signal. Data once collected was downloaded to the computer. The process of modelling and validation is then carried out using MATLAB nonlinear system identification toolbox. In this application, a model structure (NNARX) was assumed.
  • Keywords
    electric machine analysis computing; identification; induction motors; mathematics computing; neural nets; nonlinear systems; Matlab; NNARX; PRBS; black box modelling; computer-based data acquisition card; induction motor; model structure; nonlinear neural network; nonlinear system identification toolbox; pseudo random binary sequence; test data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE 2004 Annual Conference
  • Conference_Location
    Sapporo
  • Print_ISBN
    4-907764-22-7
  • Type

    conf

  • Filename
    1491557