• DocumentCode
    1343790
  • Title

    On-line stator and rotor resistance estimation for induction motors

  • Author

    Marino, Riccardo ; Peresada, Sergei ; Tomei, Patrizio

  • Author_Institution
    Dipartimento di Energia Elettrica, Rome Univ., Italy
  • Volume
    8
  • Issue
    3
  • fYear
    2000
  • fDate
    5/1/2000 12:00:00 AM
  • Firstpage
    570
  • Lastpage
    579
  • Abstract
    A ninth-order estimation algorithm is designed which provides online exponentially convergent estimates of both rotor and stator resistance for induction motors, when persistency of excitation conditions are satisfied and the stator current integrals are bounded, on the basis of rotor speed, stator voltages, and stator current measurements. Rotor flux is also asymptotically recovered. Experimental tests are reported which show that: persistency of excitation and boundedness of stator currents integrals hold in typical operating conditions; both resistance estimates converge exponentially to true values; the algorithm is implementable online by currently available digital signal processors; and the algorithm is robust with respect to modeling inaccuracies. The proposed estimation scheme is intended to improve performance and efficiency of currently available induction motor control algorithms
  • Keywords
    convergence; induction motors; parameter estimation; rotors; stators; digital signal processors; excitation persistency; induction motors; ninth-order estimation algorithm; online exponentially convergent estimates; online implementation; online rotor resistance estimation; online stator resistance estimation; resistance estimates; rotor flux; rotor speed; stator current measurements; stator voltages; Algorithm design and analysis; Current measurement; Digital signal processors; Induction motors; Integral equations; Rotors; Signal processing algorithms; Stators; Testing; Voltage;
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/87.845888
  • Filename
    845888