• DocumentCode
    592344
  • Title

    Fractional order differentiation by integration with Jacobi polynomials

  • Author

    Da-Yan Liu ; Gibaru, Olivier ; Perruquetti, W. ; Laleg-Kirati, T.

  • Author_Institution
    Electr. & Math. Sci. & Eng. Div., King Abdullah Univ. of Sci. & Technol., Thuwal, Saudi Arabia
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    624
  • Lastpage
    629
  • Abstract
    The differentiation by integration method with Jacobi polynomials was originally introduced by Mboup, Join and Fliess [22], [23]. This paper generalizes this method from the integer order to the fractional order for estimating the fractional order derivatives of noisy signals. The proposed fractional order differentiator is deduced from the Jacobi orthogonal polynomial filter and the Riemann-Liouville fractional order derivative definition. Exact and simple formula for this differentiator is given where an integral formula involving Jacobi polynomials and the noisy signal is used without complex mathematical deduction. Hence, it can be used both for continuous-time and discrete-time models. The comparison between our differentiator and the recently introduced digital fractional order Savitzky-Golay differentiator is given in numerical simulations so as to show its accuracy and robustness with respect to corrupting noises.
  • Keywords
    Jacobian matrices; continuous time systems; differentiation; discrete time systems; integration; polynomials; signal processing; Jacobi orthogonal polynomial filter; Jacobi polynomials integration; Mboup; Riemann-Liouville fractional order derivative definition; continuous-time time models; digital fractional order Savitzky-Golay differentiator; discrete-time models; fractional order derivatives; fractional order differentiation; integer order; integral formula; noisy signals; numerical simulations; Estimation error; Jacobian matrices; Noise; Noise measurement; Polynomials; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6426436
  • Filename
    6426436