Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion

Hanul Jung; Paul Tacx; Tom Oomen; Sehoon Oh

doi:10.1109/CCTA54093.2023.10253271

Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion

Hanul Jung
, Paul Tacx
, Tom Oomen
, Sehoon Oh

Department of Robotics and Mechatronics Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions.

Original language	English
Title of host publication	2023 IEEE Conference on Control Technology and Applications, CCTA 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1010-1015
Number of pages	6
ISBN (Electronic)	9798350335446
DOIs	https://doi.org/10.1109/CCTA54093.2023.10253271
State	Published - 2023
Event	2023 IEEE Conference on Control Technology and Applications, CCTA 2023 - Bridgetown, Barbados Duration: 16 Aug 2023 → 18 Aug 2023

Publication series

Name	2023 IEEE Conference on Control Technology and Applications, CCTA 2023

Conference

Conference	2023 IEEE Conference on Control Technology and Applications, CCTA 2023
Country/Territory	Barbados
City	Bridgetown
Period	16/08/23 → 18/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Access to Document

10.1109/CCTA54093.2023.10253271

Cite this

Jung, H., Tacx, P., Oomen, T., & Oh, S. (2023). Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. In 2023 IEEE Conference on Control Technology and Applications, CCTA 2023 (pp. 1010-1015). (2023 IEEE Conference on Control Technology and Applications, CCTA 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCTA54093.2023.10253271

Jung, Hanul ; Tacx, Paul ; Oomen, Tom et al. / Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. 2023 IEEE Conference on Control Technology and Applications, CCTA 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1010-1015 (2023 IEEE Conference on Control Technology and Applications, CCTA 2023).

@inproceedings{e1ce562ad27e465da33c4495cd4c9ab8,

title = "Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion",

abstract = "In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions.",

author = "Hanul Jung and Paul Tacx and Tom Oomen and Sehoon Oh",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Conference on Control Technology and Applications, CCTA 2023 ; Conference date: 16-08-2023 Through 18-08-2023",

year = "2023",

doi = "10.1109/CCTA54093.2023.10253271",

language = "English",

series = "2023 IEEE Conference on Control Technology and Applications, CCTA 2023",

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Jung, H, Tacx, P, Oomen, T & Oh, S 2023, Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. in 2023 IEEE Conference on Control Technology and Applications, CCTA 2023. 2023 IEEE Conference on Control Technology and Applications, CCTA 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1010-1015, 2023 IEEE Conference on Control Technology and Applications, CCTA 2023, Bridgetown, Barbados, 16/08/23. https://doi.org/10.1109/CCTA54093.2023.10253271

Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. / Jung, Hanul; Tacx, Paul; Oomen, Tom et al.
2023 IEEE Conference on Control Technology and Applications, CCTA 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1010-1015 (2023 IEEE Conference on Control Technology and Applications, CCTA 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion

AU - Jung, Hanul

AU - Tacx, Paul

AU - Oomen, Tom

AU - Oh, Sehoon

PY - 2023

Y1 - 2023

N2 - In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions.

AB - In this paper, novel parametric identification is addressed by the disturbance observer (DOB) relevant algorithm. To fully utilize the disturbance observer, a proper nominal model, which is a parametric model, is essential. The control performance of the DOB can be checked based on the robust stability criterion, which is related to the modeling error and the desired bandwidth of the DOB. Consequently, it is beneficial to evaluate the parametric model in the system identification procedure. Therefore, this paper proposes a novel disturbance observer-relevant system identification algorithm based on the robust stability criterion of the disturbance observer. The effectiveness of the proposed method is validated by showing the numerical simulations under specific conditions.

UR - https://www.scopus.com/pages/publications/85173854343

U2 - 10.1109/CCTA54093.2023.10253271

DO - 10.1109/CCTA54093.2023.10253271

M3 - Conference contribution

AN - SCOPUS:85173854343

T3 - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023

SP - 1010

EP - 1015

BT - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023

Y2 - 16 August 2023 through 18 August 2023

ER -

Jung H, Tacx P, Oomen T, Oh S. Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. In 2023 IEEE Conference on Control Technology and Applications, CCTA 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 1010-1015. (2023 IEEE Conference on Control Technology and Applications, CCTA 2023). doi: 10.1109/CCTA54093.2023.10253271

Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion

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