A Finite Time Convergent Least-Squares Modification of the Dynamic Regressor Extension and Mixing Algorithm

Research output: Contribution to journalConference articlepeer-review

Abstract

The recently proposed Dynamic Regressor Extension and Mixing (DREM) algorithm can be used to estimate the parameters of structured uncertainties contained in the mathematical model of a plant. In order to provide an adaptation that is less sensitive to the unavoidable mismatch between a plant and its model a least-squares based modification of the DREM estimator is proposed in this paper. The modified estimator yields significantly better estimation results as illustrated by the conducted real-world experiment and its parameter estimates also converge within finite time.
Original languageEnglish
Pages (from-to)5105-5110
JournalIFAC-PapersOnLine
Volume53
Issue number2
DOIs
Publication statusPublished - 2020
Event21st IFAC World Congress - Virtuell, Germany
Duration: 12 Jul 202017 Jul 2020

Fingerprint

Dive into the research topics of 'A Finite Time Convergent Least-Squares Modification of the Dynamic Regressor Extension and Mixing Algorithm'. Together they form a unique fingerprint.

Cite this