Comparison of online-parameter estimation methods applied to a linear belt drive system

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Daniel Beckmann
  • Mauro Hernán Riva
  • Matthias Dagen
  • Tobias Ortmaier

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks2016 European Control Conference, ECC 2016
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten364-369
Seitenumfang6
ISBN (elektronisch)9781509025916
PublikationsstatusVeröffentlicht - 2016
Veranstaltung2016 European Control Conference (ECC) - Aalborg, Dänemark
Dauer: 29 Juni 20161 Juli 2016

Abstract

In this paper a comparison of three methods for online parameter estimation is presented. The analyzed algorithms are a well known recursive least squares method (RLS), an Extended Kalman Filter (EKF) in joint state form, and an adaptive Extended Kalman Filter (aEKF). The methods' performances regarding accuracy, respond time and computing time are compared using a commercial industrial testbed, consisting of a linear belt drive for positioning tasks, an industrial servo inverter and a programmable logic controller. In addition, the online state sensitivity w.r.t. the parameters provided by the aEKF is analyzed to check the parameter excitation. These signals can be used to stop the parameter estimation for insufficient excitation.

ASJC Scopus Sachgebiete

Zitieren

Comparison of online-parameter estimation methods applied to a linear belt drive system. / Beckmann, Daniel; Riva, Mauro Hernán; Dagen, Matthias et al.
2016 European Control Conference, ECC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. S. 364-369 7810312.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Beckmann, D, Riva, MH, Dagen, M & Ortmaier, T 2016, Comparison of online-parameter estimation methods applied to a linear belt drive system. in 2016 European Control Conference, ECC 2016., 7810312, Institute of Electrical and Electronics Engineers Inc., S. 364-369, 2016 European Control Conference (ECC), Aalborg, Dänemark, 29 Juni 2016. https://doi.org/10.1109/ecc.2016.7810312
Beckmann, D., Riva, M. H., Dagen, M., & Ortmaier, T. (2016). Comparison of online-parameter estimation methods applied to a linear belt drive system. In 2016 European Control Conference, ECC 2016 (S. 364-369). Artikel 7810312 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ecc.2016.7810312
Beckmann D, Riva MH, Dagen M, Ortmaier T. Comparison of online-parameter estimation methods applied to a linear belt drive system. in 2016 European Control Conference, ECC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. S. 364-369. 7810312 doi: 10.1109/ecc.2016.7810312
Beckmann, Daniel ; Riva, Mauro Hernán ; Dagen, Matthias et al. / Comparison of online-parameter estimation methods applied to a linear belt drive system. 2016 European Control Conference, ECC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. S. 364-369
Download
@inproceedings{427cca166c8f43719e810c7a8bcd469e,
title = "Comparison of online-parameter estimation methods applied to a linear belt drive system",
abstract = "In this paper a comparison of three methods for online parameter estimation is presented. The analyzed algorithms are a well known recursive least squares method (RLS), an Extended Kalman Filter (EKF) in joint state form, and an adaptive Extended Kalman Filter (aEKF). The methods' performances regarding accuracy, respond time and computing time are compared using a commercial industrial testbed, consisting of a linear belt drive for positioning tasks, an industrial servo inverter and a programmable logic controller. In addition, the online state sensitivity w.r.t. the parameters provided by the aEKF is analyzed to check the parameter excitation. These signals can be used to stop the parameter estimation for insufficient excitation.",
author = "Daniel Beckmann and Riva, {Mauro Hern{\'a}n} and Matthias Dagen and Tobias Ortmaier",
year = "2016",
doi = "10.1109/ecc.2016.7810312",
language = "English",
pages = "364--369",
booktitle = "2016 European Control Conference, ECC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "2016 European Control Conference (ECC) ; Conference date: 29-06-2016 Through 01-07-2016",

}

Download

TY - GEN

T1 - Comparison of online-parameter estimation methods applied to a linear belt drive system

AU - Beckmann, Daniel

AU - Riva, Mauro Hernán

AU - Dagen, Matthias

AU - Ortmaier, Tobias

PY - 2016

Y1 - 2016

N2 - In this paper a comparison of three methods for online parameter estimation is presented. The analyzed algorithms are a well known recursive least squares method (RLS), an Extended Kalman Filter (EKF) in joint state form, and an adaptive Extended Kalman Filter (aEKF). The methods' performances regarding accuracy, respond time and computing time are compared using a commercial industrial testbed, consisting of a linear belt drive for positioning tasks, an industrial servo inverter and a programmable logic controller. In addition, the online state sensitivity w.r.t. the parameters provided by the aEKF is analyzed to check the parameter excitation. These signals can be used to stop the parameter estimation for insufficient excitation.

AB - In this paper a comparison of three methods for online parameter estimation is presented. The analyzed algorithms are a well known recursive least squares method (RLS), an Extended Kalman Filter (EKF) in joint state form, and an adaptive Extended Kalman Filter (aEKF). The methods' performances regarding accuracy, respond time and computing time are compared using a commercial industrial testbed, consisting of a linear belt drive for positioning tasks, an industrial servo inverter and a programmable logic controller. In addition, the online state sensitivity w.r.t. the parameters provided by the aEKF is analyzed to check the parameter excitation. These signals can be used to stop the parameter estimation for insufficient excitation.

UR - http://www.scopus.com/inward/record.url?scp=85015024166&partnerID=8YFLogxK

U2 - 10.1109/ecc.2016.7810312

DO - 10.1109/ecc.2016.7810312

M3 - Conference contribution

AN - SCOPUS:85015024166

SP - 364

EP - 369

BT - 2016 European Control Conference, ECC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 European Control Conference (ECC)

Y2 - 29 June 2016 through 1 July 2016

ER -