• DocumentCode
    1683345
  • Title

    Impedance control of robot manipulator using artificial intelligence

  • Author

    Kim, Han Me ; Chang Don Lee ; Kim, Doo Hyeong ; Park, Kyoung Taik

  • Author_Institution
    Environ. & Energy Syst. Res. Div., KIMM, Daejeon, South Korea
  • fYear
    2010
  • Firstpage
    1891
  • Lastpage
    1894
  • Abstract
    This paper deals with a sliding mode impedance control (SMIC) of end-effector of robot manipulator using a tracking control scheme and a real-time artificial intelligence algorithm based on a radial basis function neural networks(RBFNNs). To real-time estimate the design parameters of desired impedance model such as desired inertia, damping, and stiffness desired impedance, SMIC(sliding mode impedance control) with RBFNNs algorithm is proposed.
  • Keywords
    electric variables control; end effectors; radial basis function networks; variable structure systems; artificial intelligence; radial basis function neural networks; robot manipulator end effector; sliding mode impedance control; tracking control scheme; Algorithm design and analysis; Artificial neural networks; Impedance; Manipulator dynamics; Robustness; Impedance control; radial basis function neural networks; sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation and Systems (ICCAS), 2010 International Conference on
  • Conference_Location
    Gyeonggi-do
  • Print_ISBN
    978-1-4244-7453-0
  • Electronic_ISBN
    978-89-93215-02-1
  • Type

    conf

  • Filename
    5670187