• DocumentCode
    1673406
  • Title

    Intelligent tuning of a PID controller for multivariable process using immune network model based on fuzzy set

  • Author

    Kim, Dong Hwa

  • Author_Institution
    Dept. of I&C, Hanbat Nat. Univ., Seoul, South Korea
  • Volume
    1
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    93
  • Lastpage
    98
  • Abstract
    This paper suggests that the immune network algorithm based on fuzzy set can effectively be used in tuning of a PID controller for multivariable process or nonlinear process. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior
  • Keywords
    fuzzy logic; fuzzy set theory; three-term control; PID controller; antibodies; artificial immune network; fuzzy set; immune network model; intelligent tuning; multivariable process; nonlinear process; parallel decentralized processing mechanism; Artificial intelligence; Artificial neural networks; Biological neural networks; Fuzzy control; Fuzzy sets; Immune system; Intelligent networks; Intelligent systems; Process control; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2001. The 10th IEEE International Conference on
  • Conference_Location
    Melbourne, Vic.
  • Print_ISBN
    0-7803-7293-X
  • Type

    conf

  • DOI
    10.1109/FUZZ.2001.1007255
  • Filename
    1007255