Fixed-time estimation of parameters for non-persistent excitation - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue European Journal of Control Année : 2020

Fixed-time estimation of parameters for non-persistent 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 searched on a finite interval of time also based on the framework of finite-time or fixed-time converging dynamical systems. The robustness issue is analyzed and a short-time input-to-state stability property is introduced for fixed-time converging time-varying systems with a sufficient condition, which is formulated with the use of a Lyapunov function. Several estimation algorithms are proposed and compared with existing solutions. The performance of the estimators is demonstrated in numerical experiments.
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Dates et versions

hal-02196637 , version 1 (29-07-2019)

Identifiants

Citer

Jian Wang, Denis Efimov, Stanislav Aranovskiy, Alexey A. Bobtsov. Fixed-time estimation of parameters for non-persistent excitation. European Journal of Control, 2020, 55, pp.24-32. ⟨10.1016/j.ejcon.2019.07.005⟩. ⟨hal-02196637⟩
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