• DocumentCode
    2982855
  • Title

    An investigation into the feasibility of using neural networks to control turbogenerators

  • Author

    Shepstone, NM ; Harley, RG ; Jennings, G. ; Rodgerson, J.

  • Author_Institution
    Dept. of Electr. Eng., Natal Univ., Dalbridge, South Africa
  • Volume
    2
  • fYear
    1996
  • fDate
    24-27 Sep 1996
  • Firstpage
    849
  • Abstract
    This paper reports on the feasibility of using an online learning neural network as an adaptive turbogenerator controller to replace the automatic voltage regulator and the turbine governor. Results are presented which show that the neural network can control the turbogenerator at least as well as the conventional controller, but more importantly, its performance does not degrade when system conditions change
  • Keywords
    learning (artificial intelligence); machine control; neurocontrollers; power engineering computing; turbogenerators; adaptive turbogenerator controller; neural networks; online learning neural network; turbogenerators control; Adaptive control; Adaptive systems; Automatic control; Automatic voltage control; Control systems; Neural networks; Programmable control; Regulators; Turbines; Turbogenerators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AFRICON, 1996., IEEE AFRICON 4th
  • Conference_Location
    Stellenbosch
  • Print_ISBN
    0-7803-3019-6
  • Type

    conf

  • DOI
    10.1109/AFRCON.1996.563003
  • Filename
    563003