Publications

@article{Yakoub20153833b,

title = {On the Closed-Loop System Identification with Fractional Models},

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

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943789354\&doi=10.1007%2fs00034-015-0046-0\&partnerID=40\&md5=df7078429e7e8305370f4894e7a8c3d0},

doi = {10.1007/s00034-015-0046-0},

year  = {2015},

date = {2015-01-01},

journal = {Circuits, Systems, and Signal Processing},

volume = {34},

number = {12},

pages = {3833 \textendash 3860},

abstract = {In this paper, the fractional closed-loop system identification problem is addressed. Using the indirect approach, which supposes the knowledge of the controller, both coefficients and fractional orders of the process are estimated. The optimal instrumental variable method combined with a nonlinear optimization algorithm is handled to identify the fractional closed-loop transfer function. Also, two techniques are used for model selection the Akaike’s information criterion and the $$R_T^2$$RT2 criterion. The performances of the proposed scheme are illustrated by a numerical example via Monte Carlo simulation and by real electronic system identification. © 2015, Springer Science+Business Media New York.},

note = {Cited by: 20},

keywords = {Algorithms, Closed loop systems, Closed loop transfer function, Closed loops, Fractional model, Identification (control systems), Information criterion, Instrumental variable methods, Instrumental variables, Intelligent systems, Least Square, Monte Carlo methods, Non-linear optimization algorithms, Nonlinear programming, Optimization, Religious buildings},

pubstate = {published},

tppubtype = {article}

}

@article{Yakoub201525b,

title = {A bias correction method for 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-s2.0-84935026123\&doi=10.1016%2fj.jprocont.2015.05.005\&partnerID=40\&md5=5611b28f7cb96778cb11b1057ae37bc4},

doi = {10.1016/j.jprocont.2015.05.005},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Process Control},

volume = {33},

pages = {25 \textendash 36},

abstract = {Abstract In this paper, the fractional closed-loop system identification using the indirect approach is presented. A bias correction method is developed to deal with the bias problem in the continuous-time fractional closed-loop system identification. This method is based on the least squares estimator combined with the state variable filter approach. The basic idea is to eliminate the estimation bias by adding a correction term in the least squares estimates. The proposed algorithm is extended, using a nonlinear optimization algorithm, to estimate both coefficients and commensurate-order of the process. Numerical example shows the performances of the fractional order bias eliminated least squares method via Monte Carlo simulations. © 2015 Elsevier Ltd.},

note = {Cited by: 21},

keywords = {Active filters, Algorithms, Bias-correction methods, Bias-eliminated least squares methods, Closed loop systems, Commensurate-order, Continuous time systems, Electromagnetic wave attenuation, Fractional differentiation, Identification (control systems), Intelligent systems, Least Square, Least squares approximations, Least-squares estimator, Monte Carlo methods, Non-linear optimization algorithms, Nonlinear programming, Numerical methods, Optimization, Religious buildings, State-variable filters},

pubstate = {published},

tppubtype = {article}

}

@article{Chetoui2013860b,

title = {New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models},

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

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881481608\&doi=10.1016%2fj.camwa.2013.04.028\&partnerID=40\&md5=d4b467860744e79a3cee47ab860f3daf},

doi = {10.1016/j.camwa.2013.04.028},

year  = {2013},

date = {2013-01-01},

journal = {Computers and Mathematics with Applications},

volume = {66},

number = {5},

pages = {860 \textendash 872},

abstract = {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.},

note = {Cited by: 30; All Open Access, Bronze Open Access},

keywords = {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},

pubstate = {published},

tppubtype = {article}

}

@article{Chetoui2013860,

title = {New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models},

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

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881481608\&doi=10.1016%2fj.camwa.2013.04.028\&partnerID=40\&md5=d4b467860744e79a3cee47ab860f3daf},

doi = {10.1016/j.camwa.2013.04.028},

year  = {2013},

date = {2013-01-01},

journal = {Computers and Mathematics with Applications},

volume = {66},

number = {5},

pages = {860 \textendash 872},

abstract = {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.},

note = {Cited by: 30; All Open Access, Bronze Open Access},

keywords = {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},

pubstate = {published},

tppubtype = {article}

}