• DocumentCode
    1715025
  • Title

    The role of a priori knowledge of plant dynamics in neurocontroller design

  • Author

    Selinsky, J.W. ; Guez, Allon

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
  • fYear
    1989
  • Firstpage
    1754
  • Abstract
    The authors modify an earlier neurocontroller architecture so as to guarantee the performance of the neurocontroller. This architecture uses a priori knowledge of the general structure of the system´s dynamics. The knowledge is utilized for the selection of exploratory schedules to excite selected subsets of the dynamics. The controller does not require a priori knowledge of the exact system dynamics, as they are learned online, nor does it assume the existence of an explicit external teacher. The control architecture developed is not limited to tracking of a prespecified trajectory. The architecture is developed for the control of a robot manipulator
  • Keywords
    computer architecture; computerised control; learning systems; neural nets; robots; a priori knowledge; exploratory schedules; neurocontroller architecture; neurocontroller design; online learning; plant dynamics; Closed loop systems; Control system synthesis; Control systems; Dynamic scheduling; Manipulator dynamics; Neurocontrollers; Open loop systems; Robot kinematics; Stability; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • Type

    conf

  • DOI
    10.1109/CDC.1989.70455
  • Filename
    70455