Modulated Model Predictive Control for a Three-Phase Active Rectifier

Tarisciotti, Luca; Zanchetta, Pericle; Watson, Alan J.; Clare, John; Degano, Marco; Bifaretti, Stefano

doi:10.1109/tia.2014.2339397

Cited by 234 publications

(114 citation statements)

References 34 publications

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“…With this aim, the switching states S1abc(t) and S2abc(t) are computed within each sampling interval, usually in the order of tens of microseconds [9], [18], [49], [50]. The two power converters considered here are traditional three-phase two level structures in order to simplify the system configuration and demonstrate the feasibility of the proposed control approach.…”

Section: B Back-to-back Converter Applicationmentioning

confidence: 99%

“…As for the increasing number of converter switching states, above all in novel topologies, some finite-control-set MPC (FCS-MPC) approaches as well as generalized predictive control (GPC) were posed as alternatives in [10]. In particular, FCS-MPC was successfully implemented by using a reduced set of switching states as in [6], [7], [9], [14], [15]. In [16]- [21] FCS-MPC implementations were used for converters with a higher number of switching states, such as Cascaded H-Bridge and Diode Clamped converters.…”

Section: Introductionmentioning

confidence: 99%

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A Distributed Model Predictive Control Strategy for Back-to-Back Converters

Tarisciotti

Calzo

Gaeta

et al. 2016

IEEE Trans. Ind. Electron.

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Abstract-In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel Distributed Model Predictive Control, which is able to achieve the same performance of the classical Model Predictive Control whilst reducing the computational requirements of its implementation. The proposed control approach is tested on a AC/AC converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions. Index Terms-Predictive control, Nonlinear control systems, Back-to-back converters.

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Section: B Back-to-back Converter Applicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Distributed Model Predictive Control Strategy for Back-to-Back Converters

Tarisciotti

Calzo

Gaeta

et al. 2016

IEEE Trans. Ind. Electron.

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“…However, this control scheme has a crucial disadvantage of variable switching frequency, which generates a wide spectrum of harmonic distortion even at low frequencies, leading to high total harmonic distortion (THD) value. In [19], a modulated MPC for a three-phase rectifier has been proposed to reduce the harmonic distortion in currents caused by the variable switching frequency. However, the distorted grid voltages have not been considered in this study.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed scheme is based on the principle of the model predictive control, which determines the control signals by minimizing the cost function. Similar to the scheme in [19], the proposed scheme introduces weighting factors that are duty ratios of each individual active vector. Since each space vector is active for a certain duty interval during the sampling period, these duty ratios are chosen as the weighting factors for the corresponding vectors.…”

Section: Introductionmentioning

confidence: 99%

Finite Control Set–Model Predictive Control with Modulation to Mitigate Harmonic Component in Output Current for a Grid-Connected Inverter under Distorted Grid Conditions

Nguyen

Kim

2017

Energies

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This paper presents an improved current control strategy for a three-phase grid-connected inverter under distorted grid conditions. In terms of performance, it is important for a grid-connected inverter to maintain the harmonic contents of inverter output currents below the specified limit even when the grid is subject to harmonic distortion. To address this problem, this paper proposes a modulated finite control set-model predictive control (FCS-MPC) scheme, which effectively mitigates the harmonic components in output current of a grid-connected inverter. In the proposed scheme, the system behavior in the future is predicted from the system model in the discrete-time domain. Then, the cost function is selected based on the control objective of system. This cost function is minimized during the optimization process to determine the control signals that minimize the cost function. In addition, since the proposed scheme requires pure sinusoidal reference currents in the stationary frame to work successfully, the moving average filter (MAF) is employed to enhance the performance of the traditional phase lock loop (PLL). Due to the control performance of the FCS-MPC scheme as well as the harmonic disturbance rejection capability of the MAF-PLL, the proposed scheme is able to suppress the harmonic distortion even in the presence of distorted grid condition, while retaining fast transient response. Comparative simulation results of different controllers verify the effectiveness of the proposed control scheme in compensating the harmonic disturbance. To validate the practical feasibility of the proposed scheme, the whole control algorithm is implemented on a 32-bit floating-point digital signal processor (DSP) TMS320F28335 to control a 2 kW three-phase grid-connected inverter. As a result, the proposed scheme is a promising approach toward improving the current quality of a grid-connected inverter under distorted grid conditions.

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“…After its conception in the early '60s and successful implementation for industrial process control ever since, the model predictive control [1][2][3][4][5] has gained popularity in the recent past for its application in power electronics control [6][7][8]19] that has opened a host of possibilities for the control of power converters. Although this control type's use has majorly focused on converter control, the trend of its application for variable speed drives control is also on the rise [8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Finite control set and modulated model predictive flux and current control for induction motor drives

Odhano

Formentini

Zanchetta

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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-The paper presents a new implementation of direct flux and current vector control of an induction motor drive using the techniques of model predictive control. The advantages offered by predictive control are used to enhance the dynamics of direct flux vector control. To minimize the problems of variable switching frequency inherent to finite control set predictive control, an alternative approach using pulse width modulation is studied for command execution as occurs in the so-called modulated model predictive control. A comparison between finite control set and modulated model predictive control is presented and the results are also compared with the control implementation through traditional proportional-integral regulators to highlight the advantages and drawbacks of predictive control based strategies. Apart from a greater harmonic content in stator currents, the predictive control can offers control dynamics comparable with proportional-integral control while maintaining immunity against machine parameter variations and excluding the need for controller tuning.

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Modulated Model Predictive Control for a Three-Phase Active Rectifier

Cited by 234 publications

References 34 publications

A Distributed Model Predictive Control Strategy for Back-to-Back Converters

A Distributed Model Predictive Control Strategy for Back-to-Back Converters

Finite Control Set–Model Predictive Control with Modulation to Mitigate Harmonic Component in Output Current for a Grid-Connected Inverter under Distorted Grid Conditions

Finite control set and modulated model predictive flux and current control for induction motor drives

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