• DocumentCode
    515044
  • Title

    Research of Adjusted Smith Predictor Based on Immune Feedback

  • Author

    Sun, Sun Yuzhen ; Xu Chunmei ; Yu Huiqun

  • Author_Institution
    Coll. of Electr. Power & Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
  • Volume
    2
  • fYear
    2010
  • fDate
    13-14 March 2010
  • Firstpage
    1072
  • Lastpage
    1075
  • Abstract
    Immune feedback Smith predictor is a model self-modified Smith predictor with immune feedback method. In the immune feedback algorithm, the difference between Smith predictor model and actual object model is seen as antigen, the antigen can produce antibody, and antibody can adjust the model of predictor simultaneously. The immune feedback Smith predictor shows good performance as traditional Smith predictor when the object has significant time delay, and can modify the model according the actual object´s response automatically, so it have better character than traditional Smith predictor when then object have non-linear and time-varying characteristic. The simulation result prove that the Smith predictor with immune algorithm will have better Robust feature, and better adaptive when the object static characteristic change, and it can be suggested to use in real engineering projects.
  • Keywords
    artificial immune systems; delays; nonlinear control systems; time-varying systems; Smith predictor model; adjusted Smith predictor; antibody; antigen; immune feedback Smith predictor; nonlinear characteristics; object model; self-modified Smith predictor; time delay; time-varying characteristics; Automation; Cells (biology); Control systems; Delay effects; Feedback; Immune system; Prediction algorithms; Predictive models; Sun; Transfer functions; Smith predictor; immune feedback algorithm; predictor model; time delay;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
  • Conference_Location
    Changsha City
  • Print_ISBN
    978-1-4244-5001-5
  • Electronic_ISBN
    978-1-4244-5739-7
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2010.253
  • Filename
    5460204