dc.creatorAbdelrahem, Mohamed
dc.creatorHackl, Christoph
dc.creatorKennel, Ralph
dc.creatorRodriguez, Jose
dc.date.accessioned2023-07-07T18:38:55Z
dc.date.accessioned2024-05-02T14:52:27Z
dc.date.available2023-07-07T18:38:55Z
dc.date.available2024-05-02T14:52:27Z
dc.date.created2023-07-07T18:38:55Z
dc.date.issued2021
dc.identifierAbdelrahem, M.; Hackl, C.; Kennel, R.; Rodriguez, J. Low Sensitivity Predictive Control for Doubly-Fed Induction Generators BasedWind Turbine Applications. Sustainability 2021, 13, 9150. https:// doi.org/10.3390/su13169150
dc.identifier20711050
dc.identifierhttps://repositorio.unab.cl/xmlui/handle/ria/51472
dc.identifier10.3390/su13169150
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9259764
dc.description.abstractIn this paper, a deadbeat predictive control (DBPC) technique for doubly-fed induction generators (DFIGs) in wind turbine applications is proposed. The major features of DBPC scheme are its quick dynamic performance and its fixed switching frequency. However, the basic concept of DBPC is computing the reference voltage for the next sample from the mathematical model of the generator. Therefore, the DBPC is highly sensitive to variations of the parameters of the DFIG. To reduce this sensitivity, a disturbance observer is designed in this paper to improve the robustness of the proposed DBPC scheme. The proposed observer is very simple and easy to be implemented in real-time applications. The proposed DBPC strategy is implemented in the laboratory. Several experiments are performed with and without mismatches in the DFIG parameters. The experimental results proved the superiority of the proposed DBPC strategy over the traditional DBPC technique.
dc.languagees
dc.publisherMDPI
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.subjectConstant switching frequency
dc.subjectDisturbance estimator
dc.subjectDoubly-fed induction generator
dc.subjectPredictive control
dc.subjectRobustness
dc.titleLow sensitivity predictive control for doubly-fed induction generators based wind turbine applications
dc.typeArtículo


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