Torque Ripple Minimization in Switch Reluctance Motor Using Model Predictive Control for Water Pumping Application
Aguemon Dourodjayé Pierre, Agbokpanzo Richard Gilles, Houngan Kokou Théophile, Vianou Antoine
Current Journal of Applied Science and Technology · pp. 1–9 · Published 23 Jan 2019
10.9734/CJAST/2019/44861Abstract
This paper presents the torque ripple minimization in switched reluctance motor (SRM) for water pumping. The model predictive control (MPC), one of the rugged control, is used to minimize this torque ripple. According to the receding horizon, the MPC predicted the behavior of the system by generating the control signal to minimize the torque ripple. At each sampling time, an optimal control for torque ripples minimization is elaborated and only the first element is applied to the system according to the receding horizon control. The MPC minimized the real stator currents to reach the objective. The simulations on Matlab demonstrated that a very low rate of ripples could be obtained by setting the parameters of the MPC indicating the high potential of MPC in the control of SRM.
Cited by 5
Diego F. Valencia, Rasul Tarvirdilu-Asl, Cristian Garcia · IEEE Transactions on Energy Conversion · 2021
Kirti R. Chichate, Sachin R. Gore, Ajay Zadey · 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) · 2020
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