Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kroneisl, Michal | |
dc.contributor.author | Šmídl, Václav | |
dc.date.accessioned | 2021-03-08T11:00:24Z | - |
dc.date.available | 2021-03-08T11:00:24Z | - |
dc.date.issued | 2020 | |
dc.identifier.citation | KRONEISL, M. ŠMÍDL, V. Auto-commissioning of acoustic control of IM drive using bayesian optimization. In: 22th European Conference on Power Electronics and Applications (EPE’20 ECCE Europe) : /proceedings/. Piscataway: IEEE, 2020. s. „P.1"-„P.8". ISBN 978-90-75815-36-8. | cs |
dc.identifier.isbn | 978-90-75815-36-8 | |
dc.identifier.uri | 2-s2.0-85094891098 | |
dc.identifier.uri | http://hdl.handle.net/11025/42836 | |
dc.format | 8 s. | cs |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | IEEE | en |
dc.relation.ispartofseries | 22th European Conference on Power Electronics and Applications (EPE’20 ECCE Europe) : /proceedings/ | en |
dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
dc.rights | © IEEE | en |
dc.title | Auto-commissioning of acoustic control of IM drive using bayesian optimization | en |
dc.type | konferenční příspěvek | cs |
dc.type | conferenceObject | en |
dc.rights.access | restrictedAccess | en |
dc.type.version | publishedVersion | en |
dc.description.abstract-translated | Recently proposed model predictive acoustic control of an AC drive relies on availability of the transfer function from the drive current to acoustic pressure. Since such model is typically not available, we propose to consider its parameters to be unknown and use methods of Bayesian optimization to find them. Specifically, we define a acoustic control performance criterion and optimize it in an additional outer loop. A microphone is necessary in this operation to provide feedback for tuning of the parameters used in model predictive drive control algorithm. However, the microphone is removed after the tuning. Since single evaluation of the performance criteria is time consuming, we choose the Bayesian Optimization that is able to find optimal tuning with very few evaluations. | en |
dc.subject.translated | induction motor | en |
dc.subject.translated | acoustic noise | en |
dc.subject.translated | predictive control | en |
dc.subject.translated | autotuning | en |
dc.identifier.doi | 10.23919/EPE20ECCEEurope43536.2020.9215871 | |
dc.type.status | Peer-reviewed | en |
dc.identifier.obd | 43931142 | |
dc.project.ID | EF18_069/0009855/Elektrotechnické technologie s vysokým podílem vestavěné inteligence | cs |
Appears in Collections: | Konferenční příspěvky / Conference papers (RICE) Konferenční příspěvky / Conference Papers (KEV) OBD |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Kroneisl_09215871.pdf | 1,98 MB | Adobe PDF | View/Open Request a copy |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/42836
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.