• DocumentCode
    295180
  • Title

    Designing neural networks for adaptive control

  • Author

    Kaiser, Michael ; Retey, Albert ; Dillmann, Rüdiger

  • Author_Institution
    Inst. for Real-Time Comput. Syst. & Robotics, Karlsruhe Univ., Germany
  • Volume
    2
  • fYear
    1995
  • fDate
    13-15 Dec 1995
  • Firstpage
    1833
  • Abstract
    This paper discusses the design of neural networks to solve specific problems of adaptive control. In particular, it investigates the influence of typical problems arising in real-world control tasks as well as techniques for their solution that exist in the framework of neurocontrol. Based on this investigation, a systematic design method is developed. The method is exemplified for the development of an adaptive force controller for a robot manipulator
  • Keywords
    adaptive control; force control; manipulators; neurocontrollers; adaptive control; adaptive force controller; neural networks; neurocontrol; real-world control tasks; robot manipulator; systematic design method; Adaptive control; Control systems; Force control; Force sensors; Manipulators; Neural networks; Programmable control; Robot control; Robot sensing systems; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
  • Conference_Location
    New Orleans, LA
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-2685-7
  • Type

    conf

  • DOI
    10.1109/CDC.1995.480608
  • Filename
    480608