• DocumentCode
    184140
  • Title

    Convex identification of models for asymmetric hysteresis

  • Author

    Hedegard, Marcus ; Wik, Torsten

  • Author_Institution
    Dept. of Signals & Syst., Chalmers Univ. of Technol., Goteborg, Sweden
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    4753
  • Lastpage
    4758
  • Abstract
    The generalized Prandtl-Ishlinskii model (GPI) of hysteresis has a wide applicability, partly because of its capability of modelling highly asymmetric hysteresis. A disadvantage of the GPI models compared to, for example the Modified Prandtl-Ishlinskii models, has been that they have had to be identified using parametric non convex methods. Recently though, a method for non-parametric convex identification for an extended and more general GPI model was described, giving all model functions. Here, the method, which was based on input discrete equations, is briefly presented in terms of the corresponding input continuous equations. This extended model corresponds to a Preisach model and an explicit expression for this relation is derived. The method is directly applicable to data consisting of first order reversal curves, but in an application to an electrical substation equipment, it is shown that other kinds of data can also be used. The method gives significantly closer fit to this data than previous studies, and it demonstrates that non-equal left and right envelope functions are optimal.
  • Keywords
    concave programming; convex programming; identification; modelling; GPI model; Preisach model; electrical substation equipment; first order reversal curve; generalized Prandtl-Ishlinskii model; highly asymmetric hysteresis; input continuous equation; input discrete equation; model function; modified Prandtl-Ishlinskii model; nonparametric convex identification; parametric nonconvex method; Data models; Equations; Hysteresis; Mathematical model; Relays; Substations; Turning; Identification; Modeling and simulation; Nonlinear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6858953
  • Filename
    6858953