Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25494
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dc.contributor.authorBüchi, Roland-
dc.date.accessioned2022-08-25T08:12:51Z-
dc.date.available2022-08-25T08:12:51Z-
dc.date.issued2022-
dc.identifier.isbn978-3-901608-97-1de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/25494-
dc.description.abstractA large number of methods are known for system identification, which are used both in the time domain and in the frequency domain. In particular, genetic algorithms are increasingly being used today in order to determine the parameters of a model on the basis of measurements. In this article, the related method 'hill climbing' is used together with the least square criterion in order to correctly identify models of small order on the basis of measured step responses in the time domain. It is shown that the algorithm converges well for many starting values and that this method can be applied very well and efficiently for the topic of system identification.de_CH
dc.language.isoende_CH
dc.publisherASIM - Arbeitsgemeinschaft Simulationde_CH
dc.relation.ispartofseriesARGESIM Reportde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectControl theoryde_CH
dc.subjectMachine learningde_CH
dc.subject.ddc003: Systemede_CH
dc.titleA time domain approach for system identification using hill climbingde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
dc.identifier.doi10.11128/arep.20.a2014de_CH
dc.identifier.doi10.21256/zhaw-25494-
zhaw.conference.details26. Symposium Simulationstechnik (ASIM 2022), Wien, Österreich, 25.-27. Juli 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end210de_CH
zhaw.pages.start205de_CH
zhaw.parentwork.editorBreitenecker, Felix-
zhaw.parentwork.editorDeatcu, Christina-
zhaw.parentwork.editorDurak, Umut-
zhaw.parentwork.editorKörner, Andreas-
zhaw.parentwork.editorPawletta, Thorsten-
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number20de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsProceedings Langbeiträge ASIM SST 2022de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

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Büchi, R. (2022). A time domain approach for system identification using hill climbing [Conference paper]. In F. Breitenecker, C. Deatcu, U. Durak, A. Körner, & T. Pawletta (Eds.), Proceedings Langbeiträge ASIM SST 2022 (pp. 205–210). ASIM - Arbeitsgemeinschaft Simulation. https://doi.org/10.11128/arep.20.a2014
Büchi, R. (2022) ‘A time domain approach for system identification using hill climbing’, in F. Breitenecker et al. (eds) Proceedings Langbeiträge ASIM SST 2022. ASIM - Arbeitsgemeinschaft Simulation, pp. 205–210. Available at: https://doi.org/10.11128/arep.20.a2014.
R. Büchi, “A time domain approach for system identification using hill climbing,” in Proceedings Langbeiträge ASIM SST 2022, 2022, pp. 205–210. doi: 10.11128/arep.20.a2014.
BÜCHI, Roland, 2022. A time domain approach for system identification using hill climbing. In: Felix BREITENECKER, Christina DEATCU, Umut DURAK, Andreas KÖRNER und Thorsten PAWLETTA (Hrsg.), Proceedings Langbeiträge ASIM SST 2022. Conference paper. ASIM - Arbeitsgemeinschaft Simulation. 2022. S. 205–210. ISBN 978-3-901608-97-1
Büchi, Roland. 2022. “A Time Domain Approach for System Identification Using Hill Climbing.” Conference paper. In Proceedings Langbeiträge ASIM SST 2022, edited by Felix Breitenecker, Christina Deatcu, Umut Durak, Andreas Körner, and Thorsten Pawletta, 205–10. ASIM - Arbeitsgemeinschaft Simulation. https://doi.org/10.11128/arep.20.a2014.
Büchi, Roland. “A Time Domain Approach for System Identification Using Hill Climbing.” Proceedings Langbeiträge ASIM SST 2022, edited by Felix Breitenecker et al., ASIM - Arbeitsgemeinschaft Simulation, 2022, pp. 205–10, https://doi.org/10.11128/arep.20.a2014.


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