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An improved model predictive control for online PWM sequence selection applied on converter

Abstract

The Finite Control Set Model Predictive Control (FCS-MPC) technique is worldwide recognized due to its adaptability and capacity to take into account the discrete characteristics of control systems. However, it shows some limitations when directly used to control power converters, as its variable frequency spectrum, its limited current quality and its low-voltage precision for a given sample time. Therefore this paper presents an improved hybrid Pulse Width Modulation (PWM) technique based on FCS-MPC, that uses the FCS-MPC theory to select the PWM sequence applied on an inverter at each sample time. The choice on the finite set of PWM sequences is made through a trade-off between the minimization of the switching losses and load current distortion. Simulation results are presented to support the developed technique and show some promising results with appreciable reduction of the switching losses.
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Dates and versions

hal-01984942 , version 1 (17-01-2019)

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Martin Gendrin, Jean-Yves Gauthier, Xuefang Lin-Shi. An improved model predictive control for online PWM sequence selection applied on converter. 40th IEEE IECON, Oct 2014, Dallas, TX, United States. ⟨10.1109/IECON.2014.7048660⟩. ⟨hal-01984942⟩
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