• DocumentCode
    2169962
  • Title

    Neural network control of a piezo tool positioner

  • Author

    Xu, J.-H.

  • Author_Institution
    Syst. Res. Labs. Inc., Dayton, OH, USA
  • fYear
    1993
  • fDate
    14-17 Sep 1993
  • Firstpage
    333
  • Abstract
    The major technical challenge to the application of piezo crystal as an actuator is concerned with its hysteresis behavior. This would result in a nonlinear and multi-valued mapping between the actuator input and output and hence influence the desired control precision. This problem was solved by using closed-loop robust neural network control technology
  • Keywords
    actuators; machine tools; neural nets; position control; actuator; closed-loop robust neural network control technology; control precision; hysteresis behavior; multi-valued mapping; neural network control; piezo crystal; piezo tool positioner; Actuators; Assembly; Cutting tools; Magnetic hysteresis; Neural networks; Position control; Recurrent neural networks; Robust control; Robust stability; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 1993. Canadian Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-2416-1
  • Type

    conf

  • DOI
    10.1109/CCECE.1993.332324
  • Filename
    332324