• DocumentCode
    2428467
  • Title

    Estimation of induction motor speed based on artificial neural networks inversion system

  • Author

    Liu, Guohai ; Hu, Zijian ; Shen, Yue ; Zhou, Huawei ; Teng, Chenlong

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhejiang
  • fYear
    2008
  • fDate
    7-11 June 2008
  • Firstpage
    43
  • Lastpage
    47
  • Abstract
    As rotation speed is necessary for high-performance induction motor control, how to estimate the speed quickly and accurately is concerned by most scholars. On the analysis of theoretic invertibility of the induction motorpsilas mathematic model, a speed estimation based on neural networks inversion is proposed. The structure of multi-layer feed-forward neural network (MFNN) is trained by advanced backpropagation arithmetic. Also the achievement method and experiment results were given. The results show that the responses based on ANN inversion method can track the rotation speed quickly and accurately. The method proposed is effective in application.
  • Keywords
    angular velocity control; backpropagation; electric machine analysis computing; induction motors; mathematical analysis; matrix algebra; neural nets; artificial neural networks; backpropagation arithmetic; induction motor speed estimation; mathematic model; multilayer feed-forward neural network; Arithmetic; Artificial neural networks; Backpropagation; Feedforward neural networks; Feedforward systems; Induction motors; Mathematical model; Mathematics; Multi-layer neural network; Neural networks; Induction motor; Inverse System; Neural Networks; Speed Estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Signal Processing, 2008 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-2310-1
  • Electronic_ISBN
    978-1-4244-2311-8
  • Type

    conf

  • DOI
    10.1109/ICNNSP.2008.4590306
  • Filename
    4590306