Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020 |
| Erscheinungsort | Beijing, China |
| Seiten | 735-741 |
| Seitenumfang | 7 |
| ISBN (elektronisch) | 978-1-7281-6416-8 |
| Publikationsstatus | Veröffentlicht - 2020 |
Abstract
Physically motivated models of servo control systems with coupled mechanics are required for control design, simulation etc. Often, however, the effort of modelling prohibits these model-based methods in industrial applications. Therefore, all approaches of automatic modelling / model selection are naturally appealing. In this paper a procedure for model selection in frequency domain is proposed that minimizes the Kullback-Leibler distance between model and measurement while considering only those models that are practically identifiable. It aims at mechanical models of servo systems including multiple-mass resonators. Criteria for practical identifiability are derived locally from the sensitivity matrix which is calculated for different formulations of the equation error. In experiments with two industry-like testbeds the methodology proves to reveal the characteristic mechanical properties of the two setups.
Schlagwörter
- Model Selection, Frequency Domain, Servo Systems, Practical Identifiability, Sensitivity
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Ingenieurwesen (insg.)
- Maschinenbau
- Mathematik (insg.)
- Steuerung und Optimierung
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Angewandte Informatik
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2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020. Beijing, China, 2020. S. 735-741 9233569.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Frequency Domain Model Selection for Servo Systems ensuring Practical Identifiability
AU - Tantau, Mathias
AU - Perner, Lars
AU - Wielitzka, Mark
AU - Ortmaier, Tobias
N1 - Funding information: ACKNOWLEDGMENT This work was sponsored by the German Forschungsvere-inigung Antriebstechnik e.V. (FVA) and the AiF Arbeitsge-meinschaft industrieller Forschungsvereinigungen ”Otto von Guericke“ e.V.
PY - 2020
Y1 - 2020
N2 - Physically motivated models of servo control systems with coupled mechanics are required for control design, simulation etc. Often, however, the effort of modelling prohibits these model-based methods in industrial applications. Therefore, all approaches of automatic modelling / model selection are naturally appealing. In this paper a procedure for model selection in frequency domain is proposed that minimizes the Kullback-Leibler distance between model and measurement while considering only those models that are practically identifiable. It aims at mechanical models of servo systems including multiple-mass resonators. Criteria for practical identifiability are derived locally from the sensitivity matrix which is calculated for different formulations of the equation error. In experiments with two industry-like testbeds the methodology proves to reveal the characteristic mechanical properties of the two setups.
AB - Physically motivated models of servo control systems with coupled mechanics are required for control design, simulation etc. Often, however, the effort of modelling prohibits these model-based methods in industrial applications. Therefore, all approaches of automatic modelling / model selection are naturally appealing. In this paper a procedure for model selection in frequency domain is proposed that minimizes the Kullback-Leibler distance between model and measurement while considering only those models that are practically identifiable. It aims at mechanical models of servo systems including multiple-mass resonators. Criteria for practical identifiability are derived locally from the sensitivity matrix which is calculated for different formulations of the equation error. In experiments with two industry-like testbeds the methodology proves to reveal the characteristic mechanical properties of the two setups.
KW - Model Selection
KW - Frequency Domain
KW - Servo Systems
KW - Practical Identifiability
KW - Sensitivity
KW - Frequency Domain
KW - Model Selection
KW - Practical Identifiability
KW - Sensitivity
KW - Servo Systems
UR - http://www.scopus.com/inward/record.url?scp=85096558866&partnerID=8YFLogxK
U2 - 10.15488/10397
DO - 10.15488/10397
M3 - Conference contribution
SN - 978-1-7281-6417-5
SP - 735
EP - 741
BT - 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020
CY - Beijing, China
ER -