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Simulation of three-phase induction motor using nonlinear model predictive control technique

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dc.contributor.author Jasem Tamimi
dc.date.accessioned 2020-09-28T07:21:35Z
dc.date.accessioned 2022-05-22T08:53:12Z
dc.date.available 2020-09-28T07:21:35Z
dc.date.available 2022-05-22T08:53:12Z
dc.date.issued 2018-08-31
dc.identifier.citation Cogent Engineering en_US
dc.identifier.other https://doi.org/10.1080/23311916.2018.1516489
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/8166
dc.description.abstract In this paper, nonlinear model predictive control (NMPC) has been used to control an induction motor (IM). The IM model that is used in the control is third or fifth order model that is based in the vector analysis of the IM. In the third order model, the rotor speed and fluxes are considered as system states where the source frequency and the stator currents are control variables. In the fifth order, the state variables involve stator currents, rotor speed and fluxes where the control variables are stator voltages and source frequency. The formulated nonlinear optimal control problems that are used in the NMPC frameworks are not based on the field ordination technique, however, the input frequency is computed by the MPC optimizer. Moreover, the convergence or stability of the motor speed is guaranteed using stability auxiliary constraint. Simulation studies show the performance of the proposed control algorithm. en_US
dc.description.sponsorship -- en_US
dc.language.iso en en_US
dc.publisher Cogent OA en_US
dc.relation.ispartofseries 5;1
dc.subject Simulation of three-phase induction motor using nonlinear model predictive control technique en_US
dc.title Simulation of three-phase induction motor using nonlinear model predictive control technique en_US
dc.type Article en_US


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