Publications

@article{Victor2022,

title = {System identification of MISO fractional systems: Parameter and differentiation order estimation},

author = {S. Victor and A. Mayoufi and R. Malti and M. Chetoui and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127368402\&doi=10.1016%2fj.automatica.2022.110268\&partnerID=40\&md5=94d17d7d182d7bb2c6bffb4406265369},

doi = {10.1016/j.automatica.2022.110268},

issn = {00051098},

year  = {2022},

date = {2022-01-01},

journal = {Automatica},

volume = {141},

publisher = {Elsevier Ltd},

abstract = {This paper deals with continuous-time system identification of multiple-input single-output (MISO) fractional differentiation models. When differentiation orders are assumed to be known, coefficients are estimated using the simplified refined instrumental variable method for continuous-time fractional models extended to the MISO case. For unknown differentiation orders, a two-stage optimization algorithm is proposed with the developed instrumental variable for coefficient estimation and a gradient-based algorithm for differentiation order estimation. A new definition of structured-commensurability (or S-commensurability) is introduced to better cope with differentiation order estimation. Three variants of the algorithm are then proposed: (i) first, all differentiation orders are set as integer multiples of a global S-commensurate order, (ii) then, the differentiation orders are set as integer multiples of a local S-commensurate orders (one S-commensurate order for each subsystem), (iii) finally, all differentiation orders are estimated by releasing the S-commensurability constraint. The first variant has the smallest number of parameters and is used as a good initial hit for the second variant which in turn is used as a good initial hit for the third variant. Such a progressive increase of the number of parameters allows better performance of the optimization algorithm evaluated by Monte Carlo simulation analysis. © 2022 Elsevier Ltd},

note = {cited By 12},

keywords = {Continous time; Fractional model; Fractional systems; Instrumental variables; Multiple input single output systems; Multiple inputs single outputs; Optimization algorithms; Order estimation; Order optimizations; System-identification, Continuous time systems, Intelligent systems; Monte Carlo methods; Optimization; Parameter estimation; Religious buildings},

pubstate = {published},

tppubtype = {article}

}