Relaxation of Conditions for Convergence of Dynamic Regressor Extension and Mixing Procedure

Anton Glushchenko; Konstantin Lastochkin

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arXiv · 2112.04548

Relaxation of Conditions for Convergence of Dynamic Regressor Extension and Mixing Procedure

Anton Glushchenko·Konstantin Lastochkin

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Abstract

A generalization of the dynamic regressor extension and mixing procedure is proposed, which, unlike the original procedure, first, guarantees a reduction of the unknown parameter identification error if the requirement of regressor semi-finite excitation is met, and second, it ensures exponential convergence of the regression function (regressand) tracking error to zero when the regressor is semi-persistently exciting with a rank one or higher.

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Anton Glushchenko, Konstantin Lastochkin. 2021-12-08. Relaxation of Conditions for Convergence of Dynamic Regressor Extension and Mixing Procedure. https://arxiv.org/abs/2112.04548

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