• DocumentCode
    1377832
  • Title

    Ultrasonic motor servo-drive with online trained neural-network model-following controller

  • Author

    Lin, F.-J. ; Hwang, W.-J. ; Wai, R.-J.

  • Author_Institution
    Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung Li, Taiwan
  • Volume
    145
  • Issue
    2
  • fYear
    1998
  • fDate
    3/1/1998 12:00:00 AM
  • Firstpage
    105
  • Lastpage
    110
  • Abstract
    An ultrasonic servomotor (USM) drive with an online trained neural network model-following controller is proposed. First, the driving circuit for the USM, which is a two-phase chopper-inverter combination is introduced. Since the dynamic characteristics of the USM are difficult to obtain and the motor parameters are time varying, an online trained neural network model-following controller is proposed to control the rotor position of the USM. An accurate tracking response can be obtained by random initialisation of the weights and biases of the network owing to the powerful online learning capability. Moreover, the influences of parameter variations and external disturbances of the USM drive can be effectively reduced by the neural network controller
  • Keywords
    control system synthesis; learning (artificial intelligence); machine control; machine testing; machine theory; model reference adaptive control systems; motor drives; neurocontrollers; rotors; servomotors; ultrasonic motors; control design; control performance; dynamic characteristics; external disturbances; model-following controller; online learning capability; online trained neural network; parameter variations; rotor position; time varying parameters; tracking response; two-phase chopper-inverter combination; ultrasonic servomotor drive;
  • fLanguage
    English
  • Journal_Title
    Electric Power Applications, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2352
  • Type

    jour

  • DOI
    10.1049/ip-epa:19981727
  • Filename
    674844