• DocumentCode
    2056715
  • Title

    Application of multiple fuzzy-neuro force controllers in an unknown environment using genetic algorithms

  • Author

    Kiguchi, Kazuo ; Watanabe, Keigo ; Izumi, Kiyotaka ; Fukuda, Toshio

  • Author_Institution
    Dept. of Mech. Eng., Saga Univ., Japan
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2106
  • Abstract
    This paper presents an effective force control method in which multiple fuzzy-neuro force controllers are suitably and automatically combined with a proper rate in accordance with the unknown dynamics of an environment. The optimal combination rate of the fuzzy-neuro force controllers according to the environment dynamics is defined online by a neural network which is off-line trained with genetic algorithms. The effectiveness of the proposed method has been evaluated by computer simulation
  • Keywords
    adaptive control; force control; fuzzy control; fuzzy neural nets; genetic algorithms; neurocontrollers; robot dynamics; adaptive control; force control; fuzzy control; fuzzy neural network; genetic algorithms; neurocontrol; robot dynamics; Automatic control; Force control; Genetics; Humans; Jacobian matrices; Manipulator dynamics; Neural networks; Optimal control; Robot control; Robot kinematics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-5886-4
  • Type

    conf

  • DOI
    10.1109/ROBOT.2000.846340
  • Filename
    846340