On fixed-time parameter estimation under interval excitation
Résumé
The problem of estimation in the linear regression model is studied under the hypothesis that the regressor may be excited on a limited initial interval of time only. Then the estimation solution is based on the framework of finite-time or fixed-time converging dynamical systems. Two estimation algorithms are proposed. The robustness is analyzed using the notion of short-time input-to-state stability property with the use of a Lyapunov function. The performance of the estimators is demonstrated in numerical experiments.
Domaines
Automatique / Robotique| Origine | Fichiers produits par l'(les) auteur(s) |
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