Distinguishability Analysis for Multiple Mass Models of Servo Systems with Commissioning Sensors

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dc.identifier.uri http://dx.doi.org/10.15488/10570
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10647
dc.contributor.author Tantau, Mathias eng
dc.contributor.author Perner, Lars eng
dc.contributor.author Wielitzka, Mark eng
dc.date.accessioned 2021-03-17T15:20:31Z
dc.date.available 2021-03-17T15:20:31Z
dc.date.issued 2021
dc.identifier.citation Tantau, M.; Perner, L.; Wielitzka, M.: Distinguishability Analysis for Multiple Mass Models of Servo Systems with Commissioning Sensors. In: 2021 European Control Conference (ECC). Piscataway, NJ : IEEE, 2021, S. 2479-2486. DOI: https://doi.org/10.23919/ECC54610.2021.9654884 eng
dc.description.abstract Physically motivated models of electromechanical motion systems enable model-based control theory and facilitate system interpretation. Unfortunately, the effort of modelling restricts the usage of model-based methods in many applications. Some approaches to automatically generate models from measurements choose the best model based on minimizing the residual. These model selection attempts are limited due to ambiguities in reconstructing the internal structure from the input-output behaviour because usually motion systems have only one actuator and one sensor. Often, it is unknown if the resulting model is unique or if other models with different structure would fit equally well. The set of candidate models should be designed to contain only distinguishable models but ambiguities are often unknown to the experimenter. In this paper distinguishability is investigated systematically for a class of multiple mass models representing servo positioning systems. In the analysis a new criterion for indistinguishability is used. The benefit of additional, structural sensors on distinguishability of models is demonstrated which suggests to mount them temporarily for the commissioning phase in order to facilitate the model selection. It turns out that the best results can be achieved if synergies among sensor signals are utilized. © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. eng
dc.language.iso eng eng
dc.publisher Piscataway, NJ : IEEE
dc.relation.ispartof 2021 European Control Conference (ECC) eng
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. eng
dc.subject Model Selection eng
dc.subject Distinguishability eng
dc.subject Markov parameters eng
dc.subject Electric drives eng
dc.subject Unterscheidbarkeit ger
dc.subject Struktur- und Parameteridentifikation ger
dc.subject Zusatzsensorik ger
dc.subject elektrischer Antriebsstrang ger
dc.subject Markov Parameter ger
dc.subject.ddc 600 | Technik eng
dc.title Distinguishability Analysis for Multiple Mass Models of Servo Systems with Commissioning Sensors eng
dc.type ConferenceObject eng
dc.type Text eng
dc.relation.isbn 978-94-6384-236-5
dc.relation.doi 10.23919/ECC54610.2021.9654884
dc.description.version acceptedVersion eng
tib.accessRights frei zug�nglich eng


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