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On parameter tuning and convergence properties of the DREM procedure

Abstract : The recently proposed Dynamic Regressor Extension and Mixing (DREM) procedure has been proven to enhance transient performance in online parameter estimation and it has been successfully applied to a variety of adaptive control problems and applications. However, to use this procedure, a linear operator has to be chosen to perform the dynamic extension. A poor choice of the operator can reduce excitation of signals and hence it can compromise convergence properties. This paper presents a systematic selection of operators such that the excitation is always preserved. The paper also studies convergence conditions when the DREM procedure is combined with a least-squares estimator.
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Submitted on : Saturday, March 28, 2020 - 12:30:56 PM
Last modification on : Wednesday, November 3, 2021 - 9:40:58 AM

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Marina Korotina, Stanislav Aranovskiy, Rosane Ushirobira, Alexey Vedyakov. On parameter tuning and convergence properties of the DREM procedure. ECC 2020 - 18th European Control Conference, May 2020, Saint Petersburg, Russia. ⟨10.23919/ECC51009.2020.9143808⟩. ⟨hal-02523112⟩

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