• DocumentCode
    697668
  • Title

    Neuro-genetic PID autotuning

  • Author

    Lima, J.M. ; Azevedo, A.B. ; Duarte, N. ; Fonseca, C.M. ; Ruano, A.E. ; Fleming, P.J.

  • Author_Institution
    Fac. of Sci. & Technol., Univ. of Algarve, Faro, Portugal
  • fYear
    2001
  • fDate
    4-7 Sept. 2001
  • Firstpage
    3899
  • Lastpage
    3904
  • Abstract
    A new PID autotuning technique, involving neural networks and genetic algorithms is proposed. The validity of this approach is shown, through the results of several experiments. Special attention is given to the off-line training of one of the auto-tuner models, the criterion networks. Procedures used to obtain good training data are described.
  • Keywords
    adaptive control; genetic algorithms; neurocontrollers; self-adjusting systems; three-term control; autotuner model; genetic algorithm; neural network; neurogenetic PID autotuning technique; Artificial neural networks; Genetic algorithms; Splines (mathematics); Standards; Training; Tuning; Genetic algorithms; Neural networks; PID autotuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2001 European
  • Conference_Location
    Porto
  • Print_ISBN
    978-3-9524173-6-2
  • Type

    conf

  • Filename
    7076543
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=697668