• DocumentCode
    292423
  • Title

    Joint stick-slip friction compensation for robotic manipulators by iterative learning

  • Author

    Liu, Jing-Sin

  • Author_Institution
    Inst. of Inf. Sci., Acad. Sinica, Nankang, Taiwan
  • Volume
    1
  • fYear
    1994
  • fDate
    12-16 Sep 1994
  • Firstpage
    502
  • Abstract
    This paper studies the compensation of internal joint stick-slip friction effects for desired trajectory tracking of robotic manipulators. A PD type iterative learning control, which incorporates a stabilizing feedback control for robot dynamics, is applied to compensate for the friction. Simulations of a two-link robotic manipulator show that our friction compensation scheme is effective for different friction models whose characteristics are not exactly known a priori
  • Keywords
    compensation; dynamics; force control; friction; intelligent control; iterative methods; learning (artificial intelligence); manipulators; tracking; two-term control; PD control; dynamics; iterative learning control; joint stick-slip friction compensation; robotic manipulators; trajectory tracking; Feedback control; Force control; Friction; Lubrication; Manipulator dynamics; Motion control; Robot motion; Steady-state; Tracking; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems '94. 'Advanced Robotic Systems and the Real World', IROS '94. Proceedings of the IEEE/RSJ/GI International Conference on
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-1933-8
  • Type

    conf

  • DOI
    10.1109/IROS.1994.407431
  • Filename
    407431