• DocumentCode
    290653
  • Title

    Neurocontrol and the Youla parameterization

  • Author

    Saeks, R. ; Kaiser, J. ; Cox, C.

  • Author_Institution
    Accurate Autom. Corp., Chattanooga, TN, USA
  • fYear
    1993
  • fDate
    17-20 Oct 1993
  • Firstpage
    115
  • Abstract
    The paper presents a hybrid frequency domain/neurocontrol algorithm. Neural network techniques are used to adjust the Youla parameter (D.C. Youla et al., 1976) in an appropriately parameterized control system. The resulting neurocontroller is stable, robust, and reconfigurable. The learning algorithm is capable of choosing the order of the Youla parameter. Results are given to validate the concept
  • Keywords
    frequency-domain analysis; learning (artificial intelligence); neural net architecture; neurocontrollers; Youla parameter; Youla parameterization; hybrid frequency domain/neurocontrol algorithm; learning algorithm; neural network techniques; neurocontroller; parameterized control system; Asymptotic stability; Bandwidth; Broadband antennas; Delay; Force feedback; Neural networks; Neurocontrollers; Neurofeedback; Neurons; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
  • Conference_Location
    Le Touquet
  • Print_ISBN
    0-7803-0911-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1993.390693
  • Filename
    390693