Publications

@conference{Mayoufi20203701b,

title = {An optimal instrumental variable approach for continuous-time multiple input-single output fractional model identification},

author = {Abir Mayoufi and St\'{e}phane Victor and Rachid Malti and Manel Chetoui and Mohamed Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107518806\&doi=10.1016%2fj.ifacol.2020.12.2055\&partnerID=40\&md5=a45fe2670f212782b1c97c7adcd159c9},

doi = {10.1016/j.ifacol.2020.12.2055},

year  = {2020},

date = {2020-01-01},

journal = {IFAC-PapersOnLine},

volume = {53},

pages = {3701 \textendash 3706},

abstract = {This paper proposes an instrumental variable approach for continuous-time system identification using fractional models with multiple input single output context. This work is an extension of the simplified refined instrumental variable approach (srivcf) developed for single input-single output fractional model identification (Malti et al. (2008a); Victor et al. (2013)) to the multiple input-single output case. Monte Carlo simulation analysis is used to demonstrate the performance of the proposed approach. A study is then provided to motivate differentiation order estimation, and more specifically, commensurate order estimation. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)},

note = {Cited by: 1; All Open Access, Bronze Open Access, Green Open Access},

keywords = {Continuous time systems, Continuous-time, Fractional model, Fractional model identification, Instrumental variables, Monte Carlo methods, Multiple input single outputs, Order estimation, Refined instrumental variables, Single input single output},

pubstate = {published},

tppubtype = {conference}

}

@conference{Mayoufi20203701,

title = {An optimal instrumental variable approach for continuous-time multiple input-single output fractional model identification},

author = {Abir Mayoufi and St\'{e}phane Victor and Rachid Malti and Manel Chetoui and Mohamed Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107518806\&doi=10.1016%2fj.ifacol.2020.12.2055\&partnerID=40\&md5=a45fe2670f212782b1c97c7adcd159c9},

doi = {10.1016/j.ifacol.2020.12.2055},

year  = {2020},

date = {2020-01-01},

journal = {IFAC-PapersOnLine},

volume = {53},

pages = {3701 \textendash 3706},

abstract = {This paper proposes an instrumental variable approach for continuous-time system identification using fractional models with multiple input single output context. This work is an extension of the simplified refined instrumental variable approach (srivcf) developed for single input-single output fractional model identification (Malti et al. (2008a); Victor et al. (2013)) to the multiple input-single output case. Monte Carlo simulation analysis is used to demonstrate the performance of the proposed approach. A study is then provided to motivate differentiation order estimation, and more specifically, commensurate order estimation. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)},

note = {Cited by: 1; All Open Access, Bronze Open Access, Green Open Access},

keywords = {Continuous time systems, Continuous-time, Fractional model, Fractional model identification, Instrumental variables, Monte Carlo methods, Multiple input single outputs, Order estimation, Refined instrumental variables, Single input single output},

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}

}