Frequency Domain Model Selection for Servo Systems ensuring Practical Identifiability

Verfasst von

Mathias Tantau, Lars Perner, Mark Wielitzka, Tobias Ortmaier

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.

Details

Organisationseinheit(en): Institut für Mechatronische Systeme
Externe Organisation(en): Lenze SE
Typ: Aufsatz in Konferenzband
Seiten: 735-741
Anzahl der Seiten: 7
Publikationsdatum: 2020
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Artificial intelligence, Maschinenbau, Steuerung und Optimierung, Elektrotechnik und Elektronik, Computernetzwerke und -kommunikation, Angewandte Informatik
Elektronische Version(en): https://doi.org/10.15488/10397 (Zugang: Offen )
https://doi.org/10.1109/ICMA49215.2020.9233569 (Zugang: Geschlossen )