• DocumentCode
    436242
  • Title

    Position and force control of robot manipulators using neural networks

  • Author

    Zhao, Y. ; Cheah, C.C.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
  • Volume
    1
  • fYear
    2004
  • fDate
    1-3 Dec. 2004
  • Firstpage
    300
  • Abstract
    Most research on force control of robot manipulators has assumed that the kinematics and constraint surface are known exactly. In this paper, the position and force control problem of robots with uncertain kinematics, dynamics and constraint is addressed. An adaptive set point control law based on neural networks is proposed. Sufficient conditions for choosing the feedback gains are presented to guarantee the stability. Simulation results are presented to demonstrate the effectiveness of the proposed controller.
  • Keywords
    adaptive control; force control; manipulator kinematics; neurocontrollers; position control; adaptive set point control; constraint surface; feedback gains; force control; manipulators kinematics; neural networks; position control; robot manipulators; Adaptive control; Force control; Kinematics; Manipulator dynamics; Neural networks; Neurofeedback; Programmable control; Robots; Stability; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics, Automation and Mechatronics, 2004 IEEE Conference on
  • Print_ISBN
    0-7803-8645-0
  • Type

    conf

  • DOI
    10.1109/RAMECH.2004.1438935
  • Filename
    1438935