Direct Voltage Control of DC–DC Boost Converters Using Enumeration-Based Model Predictive Control

Καραμανάκος, Πέτρος; Geyer, Tobias; Manias, S.N.

doi:10.1109/tpel.2013.2256370

Cited by 256 publications

(105 citation statements)

References 31 publications

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“…Finite control set model predictive control (MPC) is one of the emerging techniques used for the control of power electronic converters [1,2,3,4]. Most of the control schemes calculate the duty ratio of the switching waveform by utilizing the averaged converter model, which could lead to inaccuracies [4]. Whereas, FCS-MPC has the ability to explicitly handle the discrete nature of semiconductor switches that can be either on or off.…”

Section: Introductionmentioning

confidence: 99%

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Variable frequency finite control set model predictive control of boost converter

Abid

Hasan

2017

IEICE Electron. Express

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Finite control set model predictive control (MPC) is one of the popular techniques for the control of power electronic converters. In this paper we explore the effect of sampling frequency in FCS-MPC of nonminimum phase converters. Usually a higher sampling frequency is linked to an improved performance. However, due to finite duration of prediction horizon in MPC and its dependence on sampling frequency we have observed that reducing the sampling frequency could improve the performance in terms of transients, efficiency and computational complexity. Based on these observations a variable frequency control scheme has also been proposed.

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Section: Introductionmentioning

confidence: 99%

“…Whereas, FCS-MPC has the ability to explicitly handle the discrete nature of semiconductor switches that can be either on or off. Therefore, the control action computed in FCS-MPC can be directly applied to the converter without the need of a demodulator [4].…”

Section: Introductionmentioning

confidence: 99%

Variable frequency finite control set model predictive control of boost converter

Abid

Hasan

2017

IEICE Electron. Express

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“…(For further discussion on non-minimum phase behavior in power converters, see [EM07,Ch. 9] and [KGM14]. )…”

Section: Introductionmentioning

confidence: 99%

Value function approximation for direct control of switched power converters

Moehle

Boyd

2017

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)

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We consider the problem of controlling switched-mode power converters using model predictive control. Model predictive control requires solving optimization problems in real time, limiting its application to systems with small numbers of switches and a short horizon. We propose a technique for using off-line computation to approximate the model predictive controller. This is done by dividing the planning horizon into two segments, and using a quadratic function to approximate the optimal cost over the second segment. The approximate model predictive algorithm minimizes the true cost over the first segment, and the approximate cost over the second segment, allowing the user to adjust the computational requirements by changing the length of the first segment. We conclude with two simulated examples.

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“…Nonetheless, the trade‐off between the switching loss and current distortion is the penalty to be considered in this approach . Extended prediction horizon is another solution favorable in most literatures by reason of its ability in lowering both the switching losses and harmonic distortions. However, there is an exponential increase of computational burden when the prediction horizon gets longer , which made it meet with predicament when putting into practice.…”

Section: Introductionmentioning

confidence: 99%

Current controller of three-phase VSI using FCS-MPC with optimal active and zero vector selection for balanced loss distribution and switching loss reduction

Lee

Heng

2016

Int. Trans. Electr. Energ. Syst.

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Summary High switching loss remains a predominant issue in conventional finite control set model predictive control (FCS‐MPC) for voltage source inverter, aside from the uneven distributed loss between upper switches and lower switches. While maintaining the inherent simplicity and effective reference tracking capability of conventional FCS‐MPC, a new FCS‐MPC is proposed to acquire substantial improvement in switching loss reduction by choosing the optimal zero vector and two active vectors. Selection of the two active vectors is performed by considering two legs that have maximum and minimum output voltage at particular sampling instant, while the selection of the optimal zero vector is based on the switching states of the previous sampling instant. The proposed method also ensures uniformly distributed loss in each phase as well as between upper switches and lower switches. Further switching loss reduction by selecting the appropriate weighting factor in the cost function is investigated for both the conventional and proposed methods as well. A loss model is constructed in MATLAB/SIMULINK for analyzing quantitative switching loss, conduction loss, total harmonic distortion, and number of switching. The proposed method ensured its superior performance under different load angles and sampling periods, and all the results are verified through simulation.

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Direct Voltage Control of DC–DC Boost Converters Using Enumeration-Based Model Predictive Control

Cited by 256 publications

References 31 publications

Variable frequency finite control set model predictive control of boost converter

Variable frequency finite control set model predictive control of boost converter

Value function approximation for direct control of switched power converters

Current controller of three-phase VSI using FCS-MPC with optimal active and zero vector selection for balanced loss distribution and switching loss reduction

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