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dc.contributor.authorJanouš, Štěpán
dc.contributor.authorKošan, Tomáš
dc.contributor.authorTalla, Jakub
dc.contributor.authorPeroutka, Zdeněk
dc.date.accessioned2019-12-16T11:00:13Z-
dc.date.available2019-12-16T11:00:13Z-
dc.date.issued2019
dc.identifier.citationJANOUŠ, Š., KOŠAN, T., TALLA, J., PEROUTKA, Z. Improved accuracy of model predictive control of induction motor drive using FPGA. In: Proceedings PRECEDE 2019 : 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE). Piscataway: IEEE, 2019. s. 216-221. ISBN 978-1-5386-9414-5.en
dc.identifier.isbn978-1-5386-9414-5
dc.identifier.uri2-s2.0-85069526816
dc.identifier.urihttp://hdl.handle.net/11025/36118
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofseriesProceedings PRECEDE 2019 : 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)en
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© IEEEen
dc.titleImproved accuracy of model predictive control of induction motor drive using FPGAen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedFinite control set model predictive control (FCS-MPC) is one of successful model predictive control approaches in electric drives which offers effective solution to multi variable multi criteria problems. The optimal control is found by “brute force” search over the limited set of possible control actions. Due to a discrete nature of power converters FCS-MPC is particularly well suited for use in electric drives. The performance of the control is closely related to accuracy of the model of controlled system. Conventional way of modeling electric drives is to include only simple model of the converter with ideal components with no voltage drops or effect of dead times. This simple mathematical converter description is computationally cheap enough to be implemented by conventional control hardware. On the other hand, the accuracy of the prediction is limited which may negatively impact the performance of the control. In this paper, we propose to design detailed mathematical model of the drive including the mathematical description of the inverter which allows us to address the problems associated with dead times and semiconductor voltage drops. Modeling those inverter nonlinear effects can enhance the control accuracy especially in non-nominal drive conditions (e.g. low speeds). On the other hand the computational requirements increases. We propose to use FPGA to implement the control algorithm using fixed-point arithmetics with high level of pipelining resulting in very fast execution times while keeping FPGA resources low. The performance of proposed solution is verified by simulations and experiments on the laboratory prototype of induction motor drive.en
dc.subject.translatedelectric potentialen
dc.subject.translatedfield programmable gate arraysen
dc.subject.translatedinduction motor drivesen
dc.subject.translatedinvertorsen
dc.subject.translatedmachine controlen
dc.subject.translatedmathematical analysisen
dc.subject.translatedoptimal controlen
dc.subject.translatedpower convertorsen
dc.subject.translatedpredictive controlen
dc.identifier.doi10.1109/PRECEDE.2019.8753242
dc.type.statusPeer-revieweden
dc.identifier.document-number490536300041
dc.identifier.obd43927624
dc.project.IDEF18_069/0009855/Elektrotechnické technologie s vysokým podílem vestavěné inteligencecs
dc.project.IDLO1607/RICE-NETESIS - nové technologie a koncepce pro inteligentní průmyslové systémy (NETESIS)cs
Vyskytuje se v kolekcích:Konferenční příspěvky / Conference papers (RICE)
Konferenční příspěvky / Conference papers (KEV)
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