Frequency Domain Model Selection for Servo Systems ensuring Practical Identifiability

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...

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Bibliographic Details
Published in2020 IEEE International Conference on Mechatronics and Automation (ICMA) pp. 735 - 741
Main Authors Tantau, Mathias, Wielitzka, Mark, Ortmaier, Tobias, Perner, Lars
Format Conference Proceeding
LanguageEnglish
Published IEEE 13.10.2020
Subjects
Frequency Domain
Frequency-domain analysis
Mathematical models
Mechanical factors
Mechatronics
Model Selection
Noise measurement
Numerical models
Practical Identifiability
Sensitivity
Servo Systems
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Summary: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.
ISSN:2152-744X
DOI:10.1109/ICMA49215.2020.9233569