2015 |
Yakoub, Z.; Chetoui, M.; Amairi, M.; Aoun, M. A bias correction method for fractional closed-loop system identification Article de journal Dans: Journal of Process Control, vol. 33, p. 25 – 36, 2015, (Cited by: 21). Résumé | Liens | BibTeX | Étiquettes: 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 @article{Yakoub201525b, 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. |
Publications
2015 |
A bias correction method for fractional closed-loop system identification Article de journal Dans: Journal of Process Control, vol. 33, p. 25 – 36, 2015, (Cited by: 21). |