Publications

@conference{Chetoui201990b,

title = {Instrumental variables based methods for linear systems identification with fractional models in the EIV context},

author = {Manel Chetoui and Mohamed Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075640184\&doi=10.1109%2fSSD.2019.8893265\&partnerID=40\&md5=2f59e71847ca98f45a7d71b9b46a627d},

doi = {10.1109/SSD.2019.8893265},

year  = {2019},

date = {2019-01-01},

journal = {16th International Multi-Conference on Systems, Signals and Devices, SSD 2019},

pages = {90 \textendash 95},

abstract = {In this paper a new instrumental variables methods based on the Higher-Order-Statistics (fourth order cumulants) are developed for continuous-time system identification with fractional models in the errors in variables context. The fractional orders are supposed known a priori and only the linear coefficients are estimated. The developed algorithms are compared to a fractional fourth order cumulants based least squares algorithm. Their performances are tested through a numerical example in two cases: white and colored noises affecting the input and the output measurements. © 2019 IEEE.},

note = {Cited by: 5},

keywords = {Continuous time systems, Continuous-time, Fourth-order cumulants, Fractional differentiation, Higher order statistics, Image segmentation, Instrumental variables, Least Square, Linear systems, State-variable filters},

pubstate = {published},

tppubtype = {conference}

}

@conference{Yakoub201710431b,

title = {Model-based fractional order controller design},

author = {Z. Yakoub and M. Chetoui and M. Amairi and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031827269\&doi=10.1016%2fj.ifacol.2017.08.1971\&partnerID=40\&md5=c84f02810425251e2e6444d4c36ec8dd},

doi = {10.1016/j.ifacol.2017.08.1971},

year  = {2017},

date = {2017-01-01},

journal = {IFAC-PapersOnLine},

volume = {50},

number = {1},

pages = {10431 \textendash 10436},

abstract = {This paper deals with model-based fractional order controller design. The objective is identification for controller design in order to achieve the desired closed-loop performances. Firstly, the fractional order closed-loop bias-eliminated least squares method is used to identify the process model. Then, based on the numerical optimization of a frequency-domain criterion, the fractional controller is designed. If the proposed algorithm detects any changes in the process parameters, the controller is updated to keep the same performances. A numerical example is presented to show the efficiency of the proposed scheme. © 2017},

note = {Cited by: 3; All Open Access, Bronze Open Access},

keywords = {Bias elimination, Closed loops, Controllers, Fractional differentiation, Frequency domain analysis, Identification for control, Least squares approximations, Optimization, Process control, Recursive least square (RLS)},

pubstate = {published},

tppubtype = {conference}

}

@conference{Yakoub2017271b,

title = {A comparison between the direct and the indirect fractional order closed-loop bias eliminated least squares method},

author = {Z. Yakoub and M. Chetoui and M. Amairi and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024378403\&doi=10.1109%2fSTA.2016.7951978\&partnerID=40\&md5=f96317e305a1fb9879331639139ecc89},

doi = {10.1109/STA.2016.7951978},

year  = {2017},

date = {2017-01-01},

journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},

pages = {271 \textendash 282},

abstract = {This paper deals with the fractional closed-loop system identification. A comparison between the direct and the indirect approach is processed. The fractional order bias eliminated least squares method is used to identify the fractional closed-loop transfer function. This method is founded on the ordinary least squares method and the state variable filter. A numerical example is treated to show the efficiency of each approach and discuss results. © 2016 IEEE.},

note = {Cited by: 0},

keywords = {Automation, Closed loops, Direct approach, Fractional differentiation, Identification (control systems), indirect approach, Least Square, Least squares approximations, Process control},

pubstate = {published},

tppubtype = {conference}

}

@conference{Salem2016640b,

title = {Instrumental variable based methods for continuous-time linear parameter varying system identification with fractional models},

author = {Thouraya Salem and Manel Chetoui and Mohamed Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84986183506\&doi=10.1109%2fMED.2016.7536043\&partnerID=40\&md5=42b2e04961aef2ea329989e32a842690},

doi = {10.1109/MED.2016.7536043},

year  = {2016},

date = {2016-01-01},

journal = {24th Mediterranean Conference on Control and Automation, MED 2016},

pages = {640 \textendash 645},

abstract = {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.},

note = {Cited by: 9},

keywords = {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},

pubstate = {published},

tppubtype = {conference}

}

@conference{Yakoub2015e,

title = {A direct fractional order bias eliminated least squares method for the fractional closed-loop system identification},

author = {Z. Yakoub and M. Chetoui and M. Amairi and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962688308\&doi=10.1109%2fSSD.2015.7348219\&partnerID=40\&md5=1523b25860bd1afff62b4ced5a164cdd},

doi = {10.1109/SSD.2015.7348219},

year  = {2015},

date = {2015-01-01},

journal = {12th International Multi-Conference on Systems, Signals and Devices, SSD 2015},

abstract = {The paper deals with the continuous-time fractional closed-loop system identification in a noisy output context. Both coefficients and fractional orders of the process are estimated using the direct approach. The proposed method is based on the least squares technique and the state variable filter. It is an extension of the bias eliminated least squares method to the fractional systems. It is combined to a nonlinear optimization algorithm in order to estimate both coefficients and fractional orders of the fractional process. A numerical example is presented to illustrate the performances of the proposed methods. © 2015 IEEE.},

note = {Cited by: 2},

keywords = {Algorithms, Closed loop systems, Closed loops, Continuous time systems, Continuous-time, Direct approach, Fractional differentiation, Identification (control systems), Least Square, Least squares approximations, Nonlinear programming, Numerical methods, Optimization, Religious buildings, State-variable filters},

pubstate = {published},

tppubtype = {conference}

}

@conference{Azaiez2015b,

title = {Analytic approach to design PID controller for stabilizing fractional systems with time delay},

author = {Wiem Azaiez and Manel Chetoui and Mohamed Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962690861\&doi=10.1109%2fSSD.2015.7348220\&partnerID=40\&md5=d959e533da4e888fa8ef51dfe75270b6},

doi = {10.1109/SSD.2015.7348220},

year  = {2015},

date = {2015-01-01},

journal = {12th International Multi-Conference on Systems, Signals and Devices, SSD 2015},

abstract = {The paper considers the problem of PID controller design for stabilizing fractional systems with time delay. An analytic approach developed for rational systems with time delay is extended for fractional systems with time delay. It consists in determining the stability regions in the PID controller parameters planes and choosing the optimal controller by analyzing the stability of the closed-loop corrected system using a graphical criterion, like the dual-locus diagram. The performances of the proposed approach are illustrated using two numerical examples. © 2015 IEEE.},

note = {Cited by: 1},

keywords = {Controllers, dual-locus diagram, Electric control equipment, Fractional differentiation, Fractional systems, Graphical criteria, Optimal controller, PID controller design, PID controllers, Proportional control systems, Stability regions, Three term control systems, Time delay},

pubstate = {published},

tppubtype = {conference}

}

@conference{Yakoub2014128b,

title = {A bias-eliminated least squares method for continuous-time fractional closed-loop system identification},

author = {Z. Yakoub and M. Amairi and M. Chetoui and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920520477\&doi=10.1109%2fCCA.2014.6981340\&partnerID=40\&md5=1e18e1e8dcd7b25d35f5589188cfe8a6},

doi = {10.1109/CCA.2014.6981340},

year  = {2014},

date = {2014-01-01},

journal = {2014 IEEE Conference on Control Applications, CCA. Part of 2014 IEEE Multi-conference on Systems and Control, MSC 2014},

pages = {128 \textendash 133},

abstract = {This paper deals with continuous-time fractional closed-loop system identification in a noisy output context. A bias correction method called the bias-eliminated least squares is extended for indirect approach identification of closed-loop system with fractional models. This method is based on the least squares method combined with the state variable filter and assumes that the regulator order can not be lower than the process order. The performances of the proposed method are assessed through a numerical example. © 2014 IEEE.},

note = {Cited by: 5},

keywords = {Closed loop systems, Closed loops, Continuous time systems, Continuous-time, Fractional differentiation, Identification (control systems), Least Square, Least squares approximations, Numerical methods, Religious buildings, State-variable filters},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chetoui2014b,

title = {Fourth order cumulants in EIV system identification using fractional models. An electronic application},

author = {Manel Chetoui and Magalie Thomassin and Rachid Malti and Mohamed Aoun and Mohamed Naceur Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84918524787\&doi=10.1109%2fICFDA.2014.6967436\&partnerID=40\&md5=4864e15da0b3922a4215fa5c5ac8366c},

doi = {10.1109/ICFDA.2014.6967436},

year  = {2014},

date = {2014-01-01},

journal = {2014 International Conference on Fractional Differentiation and Its Applications, ICFDA 2014},

abstract = {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.},

note = {Cited by: 0},

keywords = {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},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chetoui2014,

title = {Fourth order cumulants in EIV system identification using fractional models. An electronic application},

author = {Manel Chetoui and Magalie Thomassin and Rachid Malti and Mohamed Aoun and Mohamed Naceur Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84918524787\&doi=10.1109%2fICFDA.2014.6967436\&partnerID=40\&md5=4864e15da0b3922a4215fa5c5ac8366c},

doi = {10.1109/ICFDA.2014.6967436},

year  = {2014},

date = {2014-01-01},

journal = {2014 International Conference on Fractional Differentiation and Its Applications, ICFDA 2014},

abstract = {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.},

note = {Cited by: 0},

keywords = {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},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chetoui2013c,

title = {Fourth-order cumulants based method for continuous-time EIV fractional model identification},

author = {Manel Chetoui and Rachid Malti and Magalie Thomassin and Slaheddine Najar and Mohamed Aoun and Mohamed Naceur Abdelkrim and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883101214\&doi=10.1109%2fSSD.2013.6564119\&partnerID=40\&md5=ea605860656fc371483bf9eefe2534d0},

doi = {10.1109/SSD.2013.6564119},

year  = {2013},

date = {2013-01-01},

journal = {2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013},

abstract = {The errors-in-variables (EIV) system identification problem concerns the dynamic systems whose discrete input and output are corrupted by additive noises, that can be white, colored and/or mutually correlated. In this paper, a new estimator based on Higher-Order Statistics (fourth-order cumulants) is proposed for continuous-time system identification with fractional models. Under some assumptions on the distributional properties of the noise and noise-free signals, the fractional fourth-order cumulants based least squares (ffocls) estimator gives consistent results. A numerical example illustrates the performance of the proposed method. © 2013 IEEE.},

note = {Cited by: 4},

keywords = {Continuous time systems, Continuous-time, Continuous-time system identification, Distributional property, Errors, Errors in variables, Fourth-order cumulants, Fractional differentiation, Fractional model identification, Higher order statistics, Identification (control systems), System identification problems},

pubstate = {published},

tppubtype = {conference}

}

@conference{Chetoui2013,

title = {Fourth-order cumulants based method for continuous-time EIV fractional model identification},

author = {Manel Chetoui and Rachid Malti and Magalie Thomassin and Slaheddine Najar and Mohamed Aoun and Mohamed Naceur Abdelkrim and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883101214\&doi=10.1109%2fSSD.2013.6564119\&partnerID=40\&md5=ea605860656fc371483bf9eefe2534d0},

doi = {10.1109/SSD.2013.6564119},

year  = {2013},

date = {2013-01-01},

journal = {2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013},

abstract = {The errors-in-variables (EIV) system identification problem concerns the dynamic systems whose discrete input and output are corrupted by additive noises, that can be white, colored and/or mutually correlated. In this paper, a new estimator based on Higher-Order Statistics (fourth-order cumulants) is proposed for continuous-time system identification with fractional models. Under some assumptions on the distributional properties of the noise and noise-free signals, the fractional fourth-order cumulants based least squares (ffocls) estimator gives consistent results. A numerical example illustrates the performance of the proposed method. © 2013 IEEE.},

note = {Cited by: 4},

keywords = {Continuous time systems, Continuous-time, Continuous-time system identification, Distributional property, Errors, Errors in variables, Fourth-order cumulants, Fractional differentiation, Fractional model identification, Higher order statistics, Identification (control systems), System identification problems},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun2012b,

title = {Continuous fractional Kalman filter},

author = {Mohamed Aoun and Slaheddine Najar and Moufida Abdelhamid and Mohamed Naceur Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861605131\&doi=10.1109%2fSSD.2012.6198068\&partnerID=40\&md5=3b5a3d80fe7b60e0ca04ee80eddf2959},

doi = {10.1109/SSD.2012.6198068},

year  = {2012},

date = {2012-01-01},

journal = {International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings},

abstract = {This paper develops a new Kalman filter for linear systems described with continuous time fractional model. It extends the classical Kalman filter to deals with fractional differentiation. It is called continuous fractional Kalman Filter. The algorithm of the new filter is detailed and a suboptimal filter can be deduced. A numerical example illustrates the state estimation of a fractional model with the new filter. © 2012 IEEE.},

note = {Cited by: 4},

keywords = {Continuous time, Fractional differentiation, Fractional model, Kalman filters, Linear systems, Numerical example, State estimation, Suboptimal filter},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun2011e,

title = {An ellipsoidal set-membership parameter estimation of fractional orders systems},

author = {M. Aoun and M. Amairi and Z. Lassoued and S. Najar and M. N. Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957881899\&doi=10.1109%2fSSD.2011.5767416\&partnerID=40\&md5=f4a561276b178fc18bfc9dea1dc69866},

doi = {10.1109/SSD.2011.5767416},

year  = {2011},

date = {2011-01-01},

journal = {International Multi-Conference on Systems, Signals and Devices, SSD'11 - Summary Proceedings},

abstract = {This paper presents a new ellipsoidal set-membership method for the identification of linear fractional orders systems. It use the Optimal Bounding Ellipsoid (OBE) algorithm. When the probability distribution of the disturbances is unknown but bounded and when the differentiation orders are known, the proposed method can estimate all the feasible parameters. A numerical example shows the effectiveness of the proposed method. © 2011 IEEE.},

note = {Cited by: 4},

keywords = {Algorithms, Fogel-Huang algorithm, Fractional differentiation, Fractional systems, Identification (control systems), Numerical methods, OBE, Parameter estimation, Probability distributions, Set-membership, system identification},

pubstate = {published},

tppubtype = {conference}

}

@conference{Amairi2010246b,

title = {Guaranteed output-error identification of fractional order model},

author = {Messaoud Amairi and Slaheddine Najar and Mohamed Aoun and M. N. Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77957959879\&doi=10.1109%2fICACC.2010.5486678\&partnerID=40\&md5=529c5385abe1d52046a96f58bae0e649},

doi = {10.1109/ICACC.2010.5486678},

year  = {2010},

date = {2010-01-01},

journal = {Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010},

volume = {2},

pages = {246 \textendash 250},

abstract = {A global optimization technique for identifying an output-error fractional order model is proposed. The proposed technique use a modified version of Hansen algorithm. It is capable of estimating the fractional orders and the parameters, with guaranteed convergence. The technique is applied to identify a fractional order system in deterministic and stochastic context. © 2010 IEEE.},

note = {Cited by: 13},

keywords = {Fractional differentiation, Fractional model, Fractional order, Fractional order models, Fractional-order systems, Global optimization, Global optimization techniques, Guaranteed convergence, Identification (control systems), Interval analysis, Optimization, System identifications},

pubstate = {published},

tppubtype = {conference}

}

@conference{Abdelhamid2009,

title = {Discrete fractional Kalman filter},

author = {Moufida Abdelhamid and Mohamed Aoun and Slaheddine Najar and Mohamed Naceur Abdelhamid},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955725313\&doi=10.3182%2f20090921-3-TR-3005.00090\&partnerID=40\&md5=13ac1eb2213053d7b1a48169500ba641},

doi = {10.3182/20090921-3-TR-3005.00090},

year  = {2009},

date = {2009-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {2},

number = {PART 1},

abstract = {This paper presents a generalization of the classical discrete time Kalman filter algorithm to the case of the fractional systems. Motivations for the use of this filter are given and the algorithm is detailed. The document also shows a simple numerical example of linear state estimation. Copyright © 2007 International Federation of Automatic Control.},

note = {Cited by: 20; All Open Access, Bronze Open Access},

keywords = {Algorithms, Discrete time control systems, Discrete-time Kalman filters, Fractional differentiation, Fractional Kalman filter, Fractional kalman filters, Fractional systems, Intelligent control, Kalman filters, Linear state estimation, Numerical example, Signal processing, State estimation},

pubstate = {published},

tppubtype = {conference}

}

@conference{Abdelhamid2009b,

title = {Discrete fractional Kalman filter},

author = {Moufida Abdelhamid and Mohamed Aoun and Slaheddine Najar and Mohamed Naceur Abdelhamid},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955725313\&doi=10.3182%2f20090921-3-TR-3005.00090\&partnerID=40\&md5=13ac1eb2213053d7b1a48169500ba641},

doi = {10.3182/20090921-3-TR-3005.00090},

year  = {2009},

date = {2009-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {2},

number = {PART 1},

abstract = {This paper presents a generalization of the classical discrete time Kalman filter algorithm to the case of the fractional systems. Motivations for the use of this filter are given and the algorithm is detailed. The document also shows a simple numerical example of linear state estimation. Copyright © 2007 International Federation of Automatic Control.},

note = {Cited by: 20; All Open Access, Bronze Open Access},

keywords = {Algorithms, Discrete time control systems, Discrete-time Kalman filters, Fractional differentiation, Fractional Kalman filter, Fractional kalman filters, Fractional systems, Intelligent control, Kalman filters, Linear state estimation, Numerical example, Signal processing, State estimation},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun20031333,

title = {Orthonormal basis functions for modeling continuous-time fractional systems},

author = {Mohamed Aoun and Rachid Malti and Francois Levron and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017520336\&doi=10.1016%2fS1474-6670%2817%2934945-5\&partnerID=40\&md5=51049a0530b07591d53a06e9bfa5d400},

doi = {10.1016/S1474-6670(17)34945-5},

year  = {2003},

date = {2003-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {36},

number = {16},

pages = {1333 \textendash 1338},

abstract = {The classical Laguerre functions are known to be divergent as soon as their differentiation order is non-integer. They are hence inappropriate for representing fractional differentiation systems. A complete orthogonal basis, having fractional differentiation orders and a single pole, is synthesized. It extends the well-known definition of Laguerre functions to fractional systems. Hence a new class of fixed denominator models is provided for system identification. Fourier coefficients are computed using a least squares method. The least squares error is plotted versus the differentiation order and the pole, in an example, and shows that an optimal differentiation order may be located away from an integer number. Hence, the use of the synthesized basis is fully justitied. © 2003 International Federation of Automatic Control.},

note = {Cited by: 11; All Open Access, Bronze Open Access},

keywords = {Continuous time systems, Fourier analysis, Fourier coefficients, Fractional differentiation, Fractional systems, Identification (control systems), Laguerre filter, Laguerre functions, Least squares approximations, Least squares errors, Least squares methods, Orthogonal functions, Orthonormal basis functions, Poles, Religious buildings},

pubstate = {published},

tppubtype = {conference}

}

@conference{Malti20031663,

title = {Fractional Multimodels - Application to Heat Transfer Modeling},

author = {R. Malti and M. Aoun and J. -L. Battaglia and A. Oustaloup and K. Madani},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875296967\&doi=10.1016%2fS1474-6670%2817%2934999-6\&partnerID=40\&md5=4d376fa9be56a199ca80c932be521309},

doi = {10.1016/S1474-6670(17)34999-6},

year  = {2003},

date = {2003-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {36},

number = {16},

pages = {1663 \textendash 1668},

abstract = {This paper deals with identification of non linear systems using non linear fractional differentiation multimodels. All sub-models are described by fractional differentiation transfer functions. Performance of the newly proposed class of models is illustrated on a heat transfer process near a phase change temperature. © 2003 International Federation of Automatic Control.},

note = {Cited by: 4},

keywords = {Fractional differentiation, Fractional dynamics, Fractional order, Heat transfer model, Heat transfer performance, Heat transfer process, Identification (control systems), Linear systems, Multi-model, Multi-models, Nonlinear systems, Phase change temperature},

pubstate = {published},

tppubtype = {conference}

}

@conference{Malti20031663b,

title = {Fractional Multimodels - Application to Heat Transfer Modeling},

author = {R. Malti and M. Aoun and J. -L. Battaglia and A. Oustaloup and K. Madani},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875296967\&doi=10.1016%2fS1474-6670%2817%2934999-6\&partnerID=40\&md5=4d376fa9be56a199ca80c932be521309},

doi = {10.1016/S1474-6670(17)34999-6},

year  = {2003},

date = {2003-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {36},

number = {16},

pages = {1663 \textendash 1668},

abstract = {This paper deals with identification of non linear systems using non linear fractional differentiation multimodels. All sub-models are described by fractional differentiation transfer functions. Performance of the newly proposed class of models is illustrated on a heat transfer process near a phase change temperature. © 2003 International Federation of Automatic Control.},

note = {Cited by: 4},

keywords = {Fractional differentiation, Fractional dynamics, Fractional order, Heat transfer model, Heat transfer performance, Heat transfer process, Identification (control systems), Linear systems, Multi-model, Multi-models, Nonlinear systems, Phase change temperature},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun20031333b,

title = {Orthonormal basis functions for modeling continuous-time fractional systems},

author = {Mohamed Aoun and Rachid Malti and Francois Levron and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017520336\&doi=10.1016%2fS1474-6670%2817%2934945-5\&partnerID=40\&md5=51049a0530b07591d53a06e9bfa5d400},

doi = {10.1016/S1474-6670(17)34945-5},

year  = {2003},

date = {2003-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {36},

number = {16},

pages = {1333 \textendash 1338},

abstract = {The classical Laguerre functions are known to be divergent as soon as their differentiation order is non-integer. They are hence inappropriate for representing fractional differentiation systems. A complete orthogonal basis, having fractional differentiation orders and a single pole, is synthesized. It extends the well-known definition of Laguerre functions to fractional systems. Hence a new class of fixed denominator models is provided for system identification. Fourier coefficients are computed using a least squares method. The least squares error is plotted versus the differentiation order and the pole, in an example, and shows that an optimal differentiation order may be located away from an integer number. Hence, the use of the synthesized basis is fully justitied. © 2003 International Federation of Automatic Control.},

note = {Cited by: 11; All Open Access, Bronze Open Access},

keywords = {Continuous time systems, Fourier analysis, Fourier coefficients, Fractional differentiation, Fractional systems, Identification (control systems), Laguerre filter, Laguerre functions, Least squares approximations, Least squares errors, Least squares methods, Orthogonal functions, Orthonormal basis functions, Poles, Religious buildings},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun2002265,

title = {System identification using fractional hammerstein models},

author = {Mohamed Aoun and Rachid Malti and Olivier Cois and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945550683\&doi=10.3182%2f20020721-6-es-1901.01030\&partnerID=40\&md5=106ff8852a5dbedf91e03c25f0e7bb03},

doi = {10.3182/20020721-6-es-1901.01030},

year  = {2002},

date = {2002-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {15},

number = {1},

pages = {265 \textendash 269},

abstract = {Identification of continuous-time non-linear systems characterised by fractional order dynamics is studied. The Riemann-Liouville definition of fractional differentiation is used. A new identification method is proposed through the extension of Hammerstein-type models by allowing their linear part to belong to the class of fractional models. Fractional models are compact and so are used here to model complex dynamics with few parameters. Copyright © 2002 IFAC.},

note = {Cited by: 23},

keywords = {Automation, Continuous time systems, Fractional differentiation, Fractional model, Fractional order, Hammerstein model, Hammerstein-type models, Identification (control systems), Identification method, Linear systems, Non-linear modelling, Nonlinear systems, Riemann-liouville definitions},

pubstate = {published},

tppubtype = {conference}

}

@conference{Aoun2002265b,

title = {System identification using fractional hammerstein models},

author = {Mohamed Aoun and Rachid Malti and Olivier Cois and Alain Oustaloup},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945550683\&doi=10.3182%2f20020721-6-es-1901.01030\&partnerID=40\&md5=106ff8852a5dbedf91e03c25f0e7bb03},

doi = {10.3182/20020721-6-es-1901.01030},

year  = {2002},

date = {2002-01-01},

journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},

volume = {15},

number = {1},

pages = {265 \textendash 269},

abstract = {Identification of continuous-time non-linear systems characterised by fractional order dynamics is studied. The Riemann-Liouville definition of fractional differentiation is used. A new identification method is proposed through the extension of Hammerstein-type models by allowing their linear part to belong to the class of fractional models. Fractional models are compact and so are used here to model complex dynamics with few parameters. Copyright © 2002 IFAC.},

note = {Cited by: 23},

keywords = {Automation, Continuous time systems, Fractional differentiation, Fractional model, Fractional order, Hammerstein model, Hammerstein-type models, Identification (control systems), Identification method, Linear systems, Non-linear modelling, Nonlinear systems, Riemann-liouville definitions},

pubstate = {published},

tppubtype = {conference}

}