• DocumentCode
    3534282
  • Title

    Sensorless control of PMSM using a new efficient neural network speed estimator

  • Author

    Sperb, Elisabeth C L ; Negri, Lucas H. ; Baasch, Anna K S ; Polli, Horácio B. ; De Oliveira, José ; Nied, Ademir

  • Author_Institution
    Dept. of Electr. Eng., Santa Catarina State Univ., Joinville, Brazil
  • fYear
    2011
  • fDate
    11-13 May 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In order to reduce the cost and improve the reliability of variable speed drives, sensorless techniques for estimation rotor speed from measurement of voltage and current have been the subject of intensive research. This paper proposes a sensorless control strategy for Permanent Magnet Synchronous Motor (PMSM) control using a novel neural network algorithm. The proposed observer uses a neural network trained to learn the electrical and mechanical motor models using the current prediction error. Experiments were performed, showing that the proposed network topology and training algorithm have advantages to the classical ones currently employed in sensorless control.
  • Keywords
    electric current measurement; neurocontrollers; permanent magnet motors; rotors; sensorless machine control; synchronous motor drives; velocity control; voltage measurement; cost reduction; current measurement; current prediction error; electrical motor model; mechanical motor model; network topology; neural network speed estimator; permanent magnet synchronous motor control; rotor speed estimation; sensorless PMSM control; speed drive; voltage measurement; Equations; Estimation; Jacobian matrices; Mathematical model; Neurons; Rotors; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on
  • Conference_Location
    Malaga
  • ISSN
    2155-5516
  • Print_ISBN
    978-1-4244-9845-1
  • Electronic_ISBN
    2155-5516
  • Type

    conf

  • DOI
    10.1109/PowerEng.2011.6036447
  • Filename
    6036447