Publications

@article{Yakoub20192909b,

title = {On the fractional closed-loop linear parameter varying system identification under noise corrupted scheduling and output signal measurements},

author = {Zaineb Yakoub and Messaoud Amairi and Mohamed Aoun and Manel Chetoui},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061267074\&doi=10.1177%2f0142331218821409\&partnerID=40\&md5=74b33d7ecf26b354ee27592a193b26d9},

doi = {10.1177/0142331218821409},

year  = {2019},

date = {2019-01-01},

journal = {Transactions of the Institute of Measurement and Control},

volume = {41},

number = {10},

pages = {2909 \textendash 2921},

abstract = {It is well known that, in some industrial process identification situations, measurements can be collected from closed-loop experiments for several reasons such as stability, safety, and performance constraints. In this paper, we investigate the problem of identifying continuous-time fractional closed-loop linear parameter varying systems. The simplified refined instrumental variable method is developed to estimate both coefficients and differentiation orders. This method is established to provide consistent estimates when the output and the scheduling variable are contaminated by additive measurements noise. The proposed scheme is evaluated in comparison with other approaches in terms of a simulation example. © The Author(s) 2019.},

note = {Cited by: 3},

keywords = {Accident prevention, Calculations, Continuous time systems, Differentiation (calculus), Fractional calculus, Instrumental variables, Least Square, Linear parameters, Linear systems, Non-linear optimization, Nonlinear programming, Scheduling},

pubstate = {published},

tppubtype = {article}

}