Publication
Parameter Identification for Simplfied Set Current Predictive Control of SynRM Drives
| dc.contributor.author | Hadla, Hazem | |
| dc.contributor.author | Santos, Fernando | |
| dc.date.accessioned | 2022-05-26T07:43:23Z | |
| dc.date.available | 2022-05-26T07:43:23Z | |
| dc.date.issued | 2021-11-27 | |
| dc.description.abstract | In this work, a simplified finite set current predictive control (FS-CPC) is presented for the synchronous reluctance motor (SynRM) drive due to its fast response and simplicity. However, the prediction model of this control is obtained from a mathematical model of the motor which contains many parameters, and thus any parametric uncertainly might lead to inaccuracies of the predictive algorithm. Therefore, the online identification of the stator resistance, and inductances of the motor are implemented using the recursive least square (RLS) technique. The identification method is built in Matlab/Simulink, and the obtained simulation results reveal its strong accuracy and effectiveness. Thus, the estimation technique is seen as a good option to be selected and combined with the simplified FS-CPC of the SynRM. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.19/7257 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Interdisciplinary Conference on Mechanics Computers and Electrics | pt_PT |
| dc.subject | Synchronous reluctance motor drive | pt_PT |
| dc.subject | recursive least square technique | pt_PT |
| dc.subject | current predictive control | pt_PT |
| dc.title | Parameter Identification for Simplfied Set Current Predictive Control of SynRM Drives | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| person.familyName | Hadla | |
| person.familyName | Santos | |
| person.givenName | Hazem | |
| person.givenName | Fernando Miguel Soares Mamede dos Santos | |
| person.identifier.ciencia-id | D118-1FFC-1352 | |
| person.identifier.ciencia-id | 4215-EED9-9D17 | |
| person.identifier.orcid | 0000-0001-5154-126X | |
| person.identifier.orcid | 0000-0003-1551-4111 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 43c9e1fe-89a5-4c5d-971e-0875c5ab9f90 | |
| relation.isAuthorOfPublication | 32d2c21c-757e-4a31-b381-06931cfc6571 | |
| relation.isAuthorOfPublication.latestForDiscovery | 43c9e1fe-89a5-4c5d-971e-0875c5ab9f90 |
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