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}

}