Publications

@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}

}