Distinguishability study of 3-Mass Models for Electromechanical Motion Systems

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Tantau, M.; Helmke, C.; Lars Perner, L.; Wielitzka, M.: Distinguishability study of 3-Mass Models for Electromechanical Motion Systems. In: International Journal of Modelling, Identification and Control 36 (2020), Nr. 3, S. 175-187. DOI: https://doi.org/10.1504/IJMIC.2020.116913

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/11342

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Sum total of downloads: 65




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Abstract: 
Physically motivated models of electromechanical motion systems are required in several applications related to control design and auto-tracking, model-based fault detection, feed-forward, and simply interpretation. However, attempts to create such models automatically via structure and parameter identification struggle with ambiguities regarding the correct internal structure of the model. Designing a reasonable set of candidate models is difficult, because it is not known which models are distinguishable and which are not. This paper gives a simple to use necessary condition for indistinguishability of multiple mass models as they are used to model the control-relevant features of motion systems. In an automated way models are generated that can be created by considering elasticities at different positions in the mechanical structures. The condition is applied to these models for the case of three masses. In three examples it is shown that the criterion simplifies the subsequent structure and parameter identification considerably by reducing the number of possible models. For higher numbers of masses, however, it would become intractable.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: Article
Publishing status: acceptedVersion
Issue Date: 2020-01
Appears in Collections:Fakultät für Maschinenbau

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 20 30.77%
2 image of flag of United States United States 16 24.62%
3 image of flag of Ireland Ireland 5 7.69%
4 image of flag of France France 5 7.69%
5 image of flag of China China 4 6.15%
6 image of flag of Russian Federation Russian Federation 2 3.08%
7 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 3.08%
8 image of flag of Indonesia Indonesia 2 3.08%
9 image of flag of Czech Republic Czech Republic 2 3.08%
10 image of flag of Mexico Mexico 1 1.54%
    other countries 6 9.23%

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