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
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;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6426436