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Fixed-time estimation of parameters for non-persistent excitation

Abstract : 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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Contributor : Denis Efimov <>
Submitted on : Monday, July 29, 2019 - 10:55:21 AM
Last modification on : Monday, January 18, 2021 - 10:40:14 AM


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



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