• DocumentCode
    605297
  • Title

    Black-Box Modelling of AC-DC Rectifiers for RFID Applications Using Support Vector Regression Machines

  • Author

    Ceperic, V. ; Gielen, G. ; Baric, Adrijan

  • Author_Institution
    Fac. of Electr. Eng. & Comput., Univ. of Zagreb, Zagreb, Croatia
  • fYear
    2013
  • fDate
    10-12 April 2013
  • Firstpage
    815
  • Lastpage
    819
  • Abstract
    In this paper the use of support vector regression (SVR) machines for modelling of nonlinear dynamic behaviour of an AC-DC rectifier is presented. The use of SVR machines yields a black-box model which significantly reduces the simulation time. The simulated AC-DC rectifier is commonly found in radio-frequency identification (RFID) circuits and it is an excellent test case as it involves two substantially different time constants, the first one related to the radio-frequency signal and the second related to the rectification process. Two different AC-DC rectifier models are proposed. The first model models the DC voltage at the output of the rectifier after the transient process, i.e. it models the stationary value of the DC voltage. The second model models the transient process, i.e. the change of the output voltage as a function of time. The accuracy and the simulation speed are compared to the transistor levels simulations and it can be concluded that the SVR models are accurate and at least an order of magnitude faster than the transistor level models.
  • Keywords
    electronic engineering computing; radiofrequency identification; rectifiers; regression analysis; support vector machines; AC-DC rectifiers; RFID applications; SVR machines; black-box modelling; nonlinear dynamic behaviour; radio-frequency identification; support vector regression machines; Computational modeling; Computers; electronic circuit modelling; support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modelling and Simulation (UKSim), 2013 UKSim 15th International Conference on
  • Conference_Location
    Cambridge
  • Print_ISBN
    978-1-4673-6421-8
  • Type

    conf

  • DOI
    10.1109/UKSim.2013.104
  • Filename
    6527524