2016 |
Salem, Thouraya; Chetoui, Manel; Aoun, Mohamed 2016, (Cited by: 9). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Differential equations, Estimation, Fractional differential equations, Fractional differentiation, Identification (control systems), Instrumental variables, Intelligent systems, Linear parameter varying models, Linear parameter varying systems, Linear systems, LPV systems, Monte Carlo methods, Parameter estimation, Refined instrumental variables, Religious buildings @conference{Salem2016640b,This paper deals with continuous-time linear parameter varying (LPV) system identification with fractional models. Two variants of instrumental variables based techniques are proposed to estimate continuous-time parameters of a fractional differential equation linear parameter varying model when all fractional orders are assumed known a priori: the first one is the instrumental variables estimator based in an auxiliary model. The second one is the simplified refined instrumental variables estimator. A comparison study between the developed estimators is done via a numerical example. A Monte Carlo simulation analysis results are presented to illustrate the performances of the proposed methods in the presence of an additive output noise. © 2016 IEEE. |
Salem, Thouraya; Chetoui, Manel; Aoun, Mohamed 2016, (Cited by: 9). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Differential equations, Estimation, Fractional differential equations, Fractional differentiation, Identification (control systems), Instrumental variables, Intelligent systems, Linear parameter varying models, Linear parameter varying systems, Linear systems, LPV systems, Monte Carlo methods, Parameter estimation, Refined instrumental variables, Religious buildings @conference{Salem2016640,This paper deals with continuous-time linear parameter varying (LPV) system identification with fractional models. Two variants of instrumental variables based techniques are proposed to estimate continuous-time parameters of a fractional differential equation linear parameter varying model when all fractional orders are assumed known a priori: the first one is the instrumental variables estimator based in an auxiliary model. The second one is the simplified refined instrumental variables estimator. A comparison study between the developed estimators is done via a numerical example. A Monte Carlo simulation analysis results are presented to illustrate the performances of the proposed methods in the presence of an additive output noise. © 2016 IEEE. |
2014 |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Abdelkrim, Mohamed Naceur 2014, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Additive noise, Additives, commensurate order, Continuous time systems, Continuous-time, Differential equations, Electronic systems, Errors in variables, Fourth-order cumulants, Fractional differentiation, Higher order statistics, Identification (control systems), Nonlinear programming, Religious buildings, Signal processing @conference{Chetoui2014b,This paper considers the problem of identifying continuous-time fractional systems from noisy input/output measurements. Firstly, the differentiation orders are fixed and the differential equation coefficients are estimated using an estimator based on Higher-Order Statistics: fractional fourth-order cumulants based least squares (ffocls). Then, the commensurate order is estimated along with the differential equation coefficients using a non linear optimization technique combined to the ffocls algorithm (co-ffocls). Under some assumptions on the distributional properties of additive noises and the noise-free input signals, the developed estimators give consistent results. Hence, the noise-free input signal is assumed to be non gaussian, whereas the additive noises are assumed to be gaussian. The performances of the developed algorithms are assessed through a practical application for modeling a real electronic system. © 2014 IEEE. |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Abdelkrim, Mohamed Naceur 2014, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Additive noise, Additives, commensurate order, Continuous time systems, Continuous-time, Differential equations, Electronic systems, Errors in variables, Fourth-order cumulants, Fractional differentiation, Higher order statistics, Identification (control systems), Nonlinear programming, Religious buildings, Signal processing @conference{Chetoui2014,This paper considers the problem of identifying continuous-time fractional systems from noisy input/output measurements. Firstly, the differentiation orders are fixed and the differential equation coefficients are estimated using an estimator based on Higher-Order Statistics: fractional fourth-order cumulants based least squares (ffocls). Then, the commensurate order is estimated along with the differential equation coefficients using a non linear optimization technique combined to the ffocls algorithm (co-ffocls). Under some assumptions on the distributional properties of additive noises and the noise-free input signals, the developed estimators give consistent results. Hence, the noise-free input signal is assumed to be non gaussian, whereas the additive noises are assumed to be gaussian. The performances of the developed algorithms are assessed through a practical application for modeling a real electronic system. © 2014 IEEE. |
2013 |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Najar, Slaheddine; Abdelkrim, Mohamed Naceur; Oustaloup, Alain New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models Article de journal Dans: Computers and Mathematics with Applications, vol. 66, no. 5, p. 860 – 872, 2013, (Cited by: 30; All Open Access, Bronze Open Access). Résumé | Liens | BibTeX | Étiquettes: Algorithms, commensurate order, Differential equations, Errors, Errors in variables, Estimation, Fractional differentiation, Higher order statistics, Identification (control systems), Identification problem, Iterative least squares, Least squares algorithm, Non-linear optimization algorithms, Third-order cumulant @article{Chetoui2013860b,The errors-in-variables identification problem concerns dynamic systems in which input and output signals are contaminated by an additive noise. Several estimation methods have been proposed for identifying dynamic errors-in-variables rational models. This paper presents new consistent methods for order and coefficient estimation of continuous-time systems by errors-in-variables fractional models. First, differentiation orders are assumed to be known and only differential equation coefficients are estimated. Two estimators based on Higher-Order Statistics (third-order cumulants) are developed: the fractional third-order based least squares algorithm (ftocls) and the fractional third-order based iterative least squares algorithm (ftocils). Then, they are extended, using a nonlinear optimization algorithm, to estimate both the differential equation coefficients and the commensurate order. The performances of the proposed algorithms are illustrated with a numerical example. |
Hamdi, S. E.; Amairi, M.; Aoun, M.; Abdelkrim, M. N. Interval state observer design for fractional systems Conférence 2013, (Cited by: 2). Résumé | Liens | BibTeX | Étiquettes: Bounded errors, Design, Differential equations, Fractional differential equations, Fractional systems, Initial value problems, Interval analysis, observer, Observer-based, Prediction-correction, State estimation, State observer @conference{Hamdi2013b,This paper presents a design method for interval state observer for fractional systems in a bounded-error context. A causal observer based on prediction-correction approach is proposed. The prediction part consists on a validated solving of an Initial Value Problem (IVP) for a Fractional Differential Equation (FDE) and the correction part uses set inversion algorithm. A numerical example is presented to show the effectiveness of the proposed design method. © 2013 IEEE. |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Najar, Slaheddine; Abdelkrim, Mohamed Naceur; Oustaloup, Alain New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models Article de journal Dans: Computers and Mathematics with Applications, vol. 66, no. 5, p. 860 – 872, 2013, (Cited by: 30; All Open Access, Bronze Open Access). Résumé | Liens | BibTeX | Étiquettes: Algorithms, commensurate order, Differential equations, Errors, Errors in variables, Estimation, Fractional differentiation, Higher order statistics, Identification (control systems), Identification problem, Iterative least squares, Least squares algorithm, Non-linear optimization algorithms, Third-order cumulant @article{Chetoui2013860,The errors-in-variables identification problem concerns dynamic systems in which input and output signals are contaminated by an additive noise. Several estimation methods have been proposed for identifying dynamic errors-in-variables rational models. This paper presents new consistent methods for order and coefficient estimation of continuous-time systems by errors-in-variables fractional models. First, differentiation orders are assumed to be known and only differential equation coefficients are estimated. Two estimators based on Higher-Order Statistics (third-order cumulants) are developed: the fractional third-order based least squares algorithm (ftocls) and the fractional third-order based iterative least squares algorithm (ftocils). Then, they are extended, using a nonlinear optimization algorithm, to estimate both the differential equation coefficients and the commensurate order. The performances of the proposed algorithms are illustrated with a numerical example. |
2012 |
Chetoui, Manel; Malti, Rachid; Thomassin, Magalie; Aoun, Mohamed; Najar, Slaheddine; Oustaloup, Alain; Abdelkrim, Mohamed Naceur EIV methods for system identification with fractional models Conférence vol. 16, no. PART 1, 2012, (Cited by: 14). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Cumulants, Differential equations, Errors in variables, Fractional SVF, Higher order statistics, Identification (control systems), Iterative, Iterative methods, Least Square, Monte Carlo methods, Religious buildings @conference{Chetoui20121641b,This paper deals with continuous-time system identification with fractional models in Errors-In-Variables context. Two estimators based on Higher-Order Statistics (third-order cumulants) are proposed. A State Variable Filter approach is extended to fractional orders to compute fractional derivatives of third-order cumulants estimates. The performance of the proposed algorithms is illustrated in a numerical example. Firstly, differentiation orders are fixed and differential equation coefficients are estimated. The consistency of the proposed estimators is evaluated through a study of the tuning parameter and Monte Carlo simulations. Then, the commensurate differentiation order is optimized along with the differential equation coefficients. © 2012 IFAC. |
Chetoui, Manel; Malti, Rachid; Thomassin, Magalie; Aoun, Mohamed; Najar, Slaheddine; Oustaloup, Alain; Abdelkrim, Mohamed Naceur EIV methods for system identification with fractional models Conférence vol. 16, no. PART 1, 2012, (Cited by: 14). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Cumulants, Differential equations, Errors in variables, Fractional SVF, Higher order statistics, Identification (control systems), Iterative, Iterative methods, Least Square, Monte Carlo methods, Religious buildings @conference{Chetoui20121641,This paper deals with continuous-time system identification with fractional models in Errors-In-Variables context. Two estimators based on Higher-Order Statistics (third-order cumulants) are proposed. A State Variable Filter approach is extended to fractional orders to compute fractional derivatives of third-order cumulants estimates. The performance of the proposed algorithms is illustrated in a numerical example. Firstly, differentiation orders are fixed and differential equation coefficients are estimated. The consistency of the proposed estimators is evaluated through a study of the tuning parameter and Monte Carlo simulations. Then, the commensurate differentiation order is optimized along with the differential equation coefficients. © 2012 IFAC. |
2010 |
Amairi, M.; Aoun, M.; Najar, S.; Abdelkrim, M. N. A constant enclosure method for validating existence and uniqueness of the solution of an initial value problem for a fractional differential equation Article de journal Dans: Applied Mathematics and Computation, vol. 217, no. 5, p. 2162 – 2168, 2010, (Cited by: 18). Résumé | Liens | BibTeX | Étiquettes: Caputo fractional derivatives, Differential equations, Enclosures, Existence and uniqueness, Fractional order, Initial value problems, Initial values, Interval analysis, Nonlinear equations, Validated computing @article{Amairi20102162b,This paper presents a new method for validating existence and uniqueness of the solution of an initial value problems for fractional differential equations. An algorithm selecting a stepsize and computing a priori constant enclosure of the solution is proposed. Several illustrative examples, with linear and nonlinear fractional differential equations, are given to demonstrate the effectiveness of the method. © 2010 Elsevier Inc. All rights reserved. |
2004 |
Aoun, Mohamed; Malti, Rachid; Levron, François; Oustaloup, Alain Numerical simulations of fractional systems: An overview of existing methods and improvements Article de journal Dans: Nonlinear Dynamics, vol. 38, no. 1-4, p. 117 – 131, 2004, (Cited by: 117). Résumé | Liens | BibTeX | Étiquettes: Approximation theory, Computer simulation, Continuous time model, Differential equations, Discrete time model, Fractional calculus, Fractional model, Functions, Identification (control systems), Laplace transforms, Mathematical models, Time domain analysis @article{Aoun2004117b,An overview of the main simulation methods of fractional systems is presented. Based on Oustaloup’s recursive poles and zeros approximation of a fractional integrator in a frequency band some improvements are proposed. They take into account boundary effects around outer frequency limits and simplify the synthesis of a rational approximation by eliminating arbitrarily chosen parameters. © 2004 Kluwer Academic Publishers. |
Malti, Rachid; Aoun, Mohamed; Oustaloup, Alain Synthesis of fractional Kautz-like basis with two periodically repeating complex conjugate modes Conférence 2004, (Cited by: 19). Résumé | Liens | BibTeX | Étiquettes: Approximation theory, Differential equations, Dynamical systems, Extrapolation, Fractional calculus, Fractional derivatives, Generalized orthogonal basis (GOB), Identification (control systems), Laplace transforms, Linear control systems, Mathematical models, Model reduction, Orthogonal functions, Polynomials, Set theory, System stability, Transfer functions @conference{Malti2004835b,Fractional Kautz-like functions are synthesized extrapolating the definition of classical Kautz functions to fractional derivatives. The synthesized bases has two periodically repeating complex conjugate modes. The new basis extends the definition of the fractional Laguerre basis, by allowing the modes to be complex. An example is then provided in system identification context. |
Aoun, Mohamed; Malti, Rachid; Levron, François; Oustaloup, Alain Numerical simulations of fractional systems: An overview of existing methods and improvements Article de journal Dans: Nonlinear Dynamics, vol. 38, no. 1-4, p. 117 – 131, 2004, (Cited by: 117). Résumé | Liens | BibTeX | Étiquettes: Approximation theory, Computer simulation, Continuous time model, Differential equations, Discrete time model, Fractional calculus, Fractional model, Functions, Identification (control systems), Laplace transforms, Mathematical models, Time domain analysis @article{Aoun2004117,An overview of the main simulation methods of fractional systems is presented. Based on Oustaloup’s recursive poles and zeros approximation of a fractional integrator in a frequency band some improvements are proposed. They take into account boundary effects around outer frequency limits and simplify the synthesis of a rational approximation by eliminating arbitrarily chosen parameters. © 2004 Kluwer Academic Publishers. |
Malti, Rachid; Aoun, Mohamed; Oustaloup, Alain Synthesis of fractional Kautz-like basis with two periodically repeating complex conjugate modes Conférence 2004, (Cited by: 19). Résumé | Liens | BibTeX | Étiquettes: Approximation theory, Differential equations, Dynamical systems, Extrapolation, Fractional calculus, Fractional derivatives, Generalized orthogonal basis (GOB), Identification (control systems), Laplace transforms, Linear control systems, Mathematical models, Model reduction, Orthogonal functions, Polynomials, Set theory, System stability, Transfer functions @conference{Malti2004835,Fractional Kautz-like functions are synthesized extrapolating the definition of classical Kautz functions to fractional derivatives. The synthesized bases has two periodically repeating complex conjugate modes. The new basis extends the definition of the fractional Laguerre basis, by allowing the modes to be complex. An example is then provided in system identification context. |
2003 |
Malti, Rachid; Aoun, Mohamed; Cois, Olivier; Oustaloup, Alain; Levron, François H2 norm of fractional differential systems Conférence vol. 5 A, 2003, (Cited by: 19). Liens | BibTeX | Étiquettes: Algebra, Computer simulation, Differential equations, Differentiation (calculus), Explicit systems, Fractional differential systems, Impulse response, Laplace transforms, Mathematical models, Theorem proving, Transfer functions @conference{Malti2003729b, |
Malti, Rachid; Aoun, Mohamed; Cois, Olivier; Oustaloup, Alain; Levron, François H2 norm of fractional differential systems Conférence vol. 5 A, 2003, (Cited by: 19). Liens | BibTeX | Étiquettes: Algebra, Computer simulation, Differential equations, Differentiation (calculus), Explicit systems, Fractional differential systems, Impulse response, Laplace transforms, Mathematical models, Theorem proving, Transfer functions @conference{Malti2003729, |
Publications
2016 |
2016, (Cited by: 9). |
2016, (Cited by: 9). |
2014 |
2014, (Cited by: 0). |
2014, (Cited by: 0). |
2013 |
New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models Article de journal Dans: Computers and Mathematics with Applications, vol. 66, no. 5, p. 860 – 872, 2013, (Cited by: 30; All Open Access, Bronze Open Access). |
Interval state observer design for fractional systems Conférence 2013, (Cited by: 2). |
New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models Article de journal Dans: Computers and Mathematics with Applications, vol. 66, no. 5, p. 860 – 872, 2013, (Cited by: 30; All Open Access, Bronze Open Access). |
2012 |
EIV methods for system identification with fractional models Conférence vol. 16, no. PART 1, 2012, (Cited by: 14). |
EIV methods for system identification with fractional models Conférence vol. 16, no. PART 1, 2012, (Cited by: 14). |
2010 |
A constant enclosure method for validating existence and uniqueness of the solution of an initial value problem for a fractional differential equation Article de journal Dans: Applied Mathematics and Computation, vol. 217, no. 5, p. 2162 – 2168, 2010, (Cited by: 18). |
2004 |
Numerical simulations of fractional systems: An overview of existing methods and improvements Article de journal Dans: Nonlinear Dynamics, vol. 38, no. 1-4, p. 117 – 131, 2004, (Cited by: 117). |
Synthesis of fractional Kautz-like basis with two periodically repeating complex conjugate modes Conférence 2004, (Cited by: 19). |
Numerical simulations of fractional systems: An overview of existing methods and improvements Article de journal Dans: Nonlinear Dynamics, vol. 38, no. 1-4, p. 117 – 131, 2004, (Cited by: 117). |
Synthesis of fractional Kautz-like basis with two periodically repeating complex conjugate modes Conférence 2004, (Cited by: 19). |
2003 |
H2 norm of fractional differential systems Conférence vol. 5 A, 2003, (Cited by: 19). |
H2 norm of fractional differential systems Conférence vol. 5 A, 2003, (Cited by: 19). |