• DocumentCode
    2789627
  • Title

    Sliding Mode MRAS Speed Sensorless Vector Control for Submersible Motor

  • Author

    Shan Bai ; He Wang

  • Author_Institution
    Sch. of Electr. Eng., Shenyang Univ. of Technol., Shenyang, China
  • fYear
    2015
  • fDate
    24-26 April 2015
  • Firstpage
    916
  • Lastpage
    920
  • Abstract
    In consideration of the difficulty to install speed sensor result from special high temperature working environment of submersible motor, in this paper, a method of sliding mode model reference adaptive observer(SMMRAS) is used to estimate the speed of sensor less vector controlled submersible motor. This method combines variable structure control with model reference adaptive system (MRAS) to improve the accuracy of speed identification, and testability and speediness capability of the system are proved by Yaupon theory. The model of the speed-sensor less vector control system of induction motor is built by MatLab/Simulink. Theoretical analysis and the MATLAB simulation results show that the proposed method used in the system for speed identification has rapid response, and the static and dynamic performance is also perfect.
  • Keywords
    adaptive control; adaptive systems; angular velocity control; induction motors; observers; sensorless machine control; variable structure systems; Lyapunov theory; MATLAB simulation; SMMRAS; Simulink; dynamic performance; induction motor; sliding mode MRAS speed sensorless vector control; sliding mode model reference adaptive observer; speed identification; stability; static performance; submersible motor; theoretical analysis; Adaptation models; Adaptive systems; Induction motors; Mathematical model; Rotors; Switches; model reference adaptive system (MRAS); speed estimation; speed sensorless; submersible motor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-6849-0
  • Type

    conf

  • DOI
    10.1109/ICISCE.2015.208
  • Filename
    7120748