Model Selection ensuring Practical Identifiability for Models of Electric Drives with Coupled Mechanics

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dc.identifier.uri http://dx.doi.org/10.15488/10400
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10474
dc.contributor.author Tantau, Mathias eng
dc.contributor.author Popp, Eduard eng
dc.contributor.author Perner, Lars eng
dc.contributor.author Wielitzka, Mark eng
dc.contributor.author Ortmaier, Tobias eng
dc.date.accessioned 2021-02-16T09:38:48Z
dc.date.available 2021-02-16T09:38:48Z
dc.date.issued 2020-07-11
dc.identifier.citation Tantau, M.; Popp, E.; Perner, L.; Wielitzka, M.; Ortmaier, T.: Model Selection ensuring Practical Identifiability for Models of Electric Drives with Coupled Mechanics. In: IFAC-PapersOnLine 53 (2020), Nr. 2, S. 8853-8859. DOI: https://doi.org/10.1016/j.ifacol.2020.12.1400 eng
dc.description.abstract Physically motivated models of electric drive trains with coupled mechanics are ubiquitous in industry for control design, simulation, feed-forward, model-based fault diagnosis etc. Often, however, the effort of model building prohibits these model-based methods. In this paper an automated model selection strategy is proposed for dynamic simulation models that not only optimizes the accuracy of the fit but also ensures practical identifiability of model parameters during structural optimization. Practical identifiability is crucial for physically motivated, interpretable models as opposed to pure prediction and inference applications. Our approach extends structural optimization considering practical identifiability to nonlinear models. In spite of the nonlinearity, local and linear criteria are evaluated, the integrity of which is investigated exemplarily. The methods are validated experimentally on a stacker crane. eng
dc.language.iso eng eng
dc.publisher Frankfurt ; München [u.a.] : Elsevier
dc.relation.ispartofseries IFAC-PapersOnLine 53 (2020), Nr. 2
dc.rights CC BY-NC-ND 4.0 Unported eng
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/ eng
dc.subject model selection eng
dc.subject structure and parameter identi cation eng
dc.subject practical identi ability eng
dc.subject sensitivity analysis eng
dc.subject.ddc 600 | Technik eng
dc.title Model Selection ensuring Practical Identifiability for Models of Electric Drives with Coupled Mechanics eng
dc.type article eng
dc.type conferenceObject eng
dc.type Text
dc.relation.essn 2405-8963
dc.description.version acceptedVersion eng
tib.accessRights frei zug�nglich eng


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