• DocumentCode
    329393
  • Title

    Vibration control of 2-mass system using a neural network torsional torque estimator

  • Author

    Song, Joong-ho ; Lee, Kyo-Beum ; Choy, Ick ; Kim, Kwang-Bae ; Choi, Joo-Yeop ; Lee, Kwang-Won

  • Author_Institution
    KIST, Seoul, South Korea
  • Volume
    3
  • fYear
    1998
  • fDate
    31 Aug-4 Sep 1998
  • Firstpage
    1785
  • Abstract
    A new control scheme using a torsional torque estimator based on a neural network is proposed and investigated for improving control characteristics of the high-performance motion control system. This control method presents better performance in the corresponding speed vibration response, compared with the disturbance observer-based control method. This result comes from the fact that the proposed neural network estimator keeps the self-learning capability, whereas the disturbance observer based torque estimator with the low pass filter should adjust the time constant of the adopted filter according to the natural resonance frequency determined by considering the system parameters varied. The simulation results show the validity of the proposed control scheme
  • Keywords
    control system analysis; control system synthesis; motion control; neurocontrollers; parameter estimation; torque control; torsion; unsupervised learning; vibration control; control design; control performance; control simulation; motion control system; neural network; self-learning capability; speed vibration response; torsional torque estimator; two-mass system vibration control; Control systems; Frequency estimation; Low pass filters; Motion control; Motion estimation; Neural networks; Resonance; Resonant frequency; Torque control; Vibration control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE
  • Conference_Location
    Aachen
  • Print_ISBN
    0-7803-4503-7
  • Type

    conf

  • DOI
    10.1109/IECON.1998.722960
  • Filename
    722960