2016 |
Salem, Thouraya; Chetoui, Manel; Aoun, Mohamed 2016, (Cited by: 9). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Differential equations, Estimation, Fractional differential equations, Fractional differentiation, Identification (control systems), Instrumental variables, Intelligent systems, Linear parameter varying models, Linear parameter varying systems, Linear systems, LPV systems, Monte Carlo methods, Parameter estimation, Refined instrumental variables, Religious buildings @conference{Salem2016640b, This paper deals with continuous-time linear parameter varying (LPV) system identification with fractional models. Two variants of instrumental variables based techniques are proposed to estimate continuous-time parameters of a fractional differential equation linear parameter varying model when all fractional orders are assumed known a priori: the first one is the instrumental variables estimator based in an auxiliary model. The second one is the simplified refined instrumental variables estimator. A comparison study between the developed estimators is done via a numerical example. A Monte Carlo simulation analysis results are presented to illustrate the performances of the proposed methods in the presence of an additive output noise. © 2016 IEEE. |
2013 |
Hamdi, S. E.; Amairi, M.; Aoun, M.; Abdelkrim, M. N. Interval state observer design for fractional systems Conférence 2013, (Cited by: 2). Résumé | Liens | BibTeX | Étiquettes: Bounded errors, Design, Differential equations, Fractional differential equations, Fractional systems, Initial value problems, Interval analysis, observer, Observer-based, Prediction-correction, State estimation, State observer @conference{Hamdi2013b, This paper presents a design method for interval state observer for fractional systems in a bounded-error context. A causal observer based on prediction-correction approach is proposed. The prediction part consists on a validated solving of an Initial Value Problem (IVP) for a Fractional Differential Equation (FDE) and the correction part uses set inversion algorithm. A numerical example is presented to show the effectiveness of the proposed design method. © 2013 IEEE. |
Publications
2016 |
2016, (Cited by: 9). |
2013 |
Interval state observer design for fractional systems Conférence 2013, (Cited by: 2). |