Identification of fractional order systems using modulating functions method

The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.

[1]  Olivier Gibaru,et al.  Parameters estimation of a noisy sinusoidal signal with time-varying amplitude , 2011, 2011 19th Mediterranean Conference on Control & Automation (MED).

[2]  Liuping Wang,et al.  Identification of Continuous-time Models from Sampled Data , 2008 .

[3]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[4]  Olivier Gibaru,et al.  Non-asymptotic fractional order differentiators via an algebraic parametric method , 2012, 2012 1st International Conference on Systems and Computer Science (ICSCS).

[5]  Hebertt Sira-Ramírez,et al.  Closed-loop parametric identification for continuous-time linear systems via new algebraic techniques , 2007 .

[6]  J. Sabatier,et al.  TUTORIAL ON SYSTEM IDENTIFICATION USING FRACTIONAL DIFFERENTIATION MODELS , 2006 .

[7]  Alain Oustaloup,et al.  Fractional system identification for lead acid battery state of charge estimation , 2006, Signal Process..

[8]  Alain Oustaloup,et al.  Non Integer Model from Modal Decomposition for Time Domain System Identification , 2000 .

[9]  Alina Voda,et al.  Recursive prediction error identification of fractional order models , 2012 .

[10]  H. Srivastava,et al.  Theory and Applications of Fractional Differential Equations , 2006 .

[11]  Dayan Liu,et al.  An error analysis in the algebraic estimation of a noisy sinusoidal signal , 2008, 2008 16th Mediterranean Conference on Control and Automation.

[12]  Thierry Poinot,et al.  Fractional modelling and identification of thermal systems , 2011, Signal Process..

[13]  Yangquan Chen,et al.  Digital Fractional Order Savitzky-Golay Differentiator , 2011, IEEE Transactions on Circuits and Systems II: Express Briefs.

[14]  M. Fliess,et al.  An algebraic framework for linear identification , 2003 .

[15]  Alain Oustaloup,et al.  Synthesis of fractional Laguerre basis for system approximation , 2007, Autom..

[16]  T. Janiczek,et al.  Generalization of the modulating functions method into the fractional differential equations , 2010 .

[17]  A. Oustaloup,et al.  Modeling and identification of a non integer order system , 1999, 1999 European Control Conference (ECC).

[18]  T. Kaczorek,et al.  Fractional Differential Equations , 2015 .

[19]  Michel Fliess,et al.  Analyse non standard du bruit , 2006, ArXiv.

[20]  Olivier Gibaru,et al.  Fractional order differentiation by integration with Jacobi polynomials , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[21]  Heinz A. Preisig,et al.  Theory and application of the modulating function method—I. Review and theory of the method and theory of the spline-type modulating functions , 1993 .

[22]  A. Oustaloup,et al.  Fractional state variable filter for system identification by fractional model , 2001, 2001 European Control Conference (ECC).

[23]  Olivier Gibaru,et al.  Error analysis of Jacobi derivative estimators for noisy signals , 2011, Numerical Algorithms.

[24]  K. Miller,et al.  An Introduction to the Fractional Calculus and Fractional Differential Equations , 1993 .

[25]  M. Mboup Parameter estimation for signals described by differential equations , 2009 .

[26]  Marvin Shinbrot On the analysis of linear and nonlinear dynamical systems from transient-response data , 1954 .

[27]  Igor Podlubny,et al.  ADJOINT FRACTIONAL DIFFERENTIAL EXPRESSIONS AND OPERATORS , 2007 .

[28]  Vicente Feliú Batlle,et al.  An algebraic frequency estimator for a biased and noisy sinusoidal signal , 2007, Signal Process..

[29]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[30]  Wilfrid Perruquetti,et al.  An algebraic approach for human posture estimation in the sagittal plane using accelerometer noisy signal , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[31]  Wilfrid Perruquetti,et al.  Algebraic parameter estimation of a biased sinusoidal waveform signal from noisy data , 2012 .

[32]  J. Gabano,et al.  Identification of a thermal system using continuous linear parameter-varying fractional modelling , 2011 .