FPGA-Based Experimental Investigation of a Quasi-Centralized Model Predictive Control for Back-to-Back Converters

Zhenbin Zhang, Fengxiang Wang, Tongjing Sun, José Rodríguez, Ralph Kennel

Resultado de la investigación: Article

40 Citas (Scopus)

Resumen

Voltage source back-to-back power converters are widely used in grid-tied applications. This paper presents a quasi-centralized direct model predictive control (QC-DMPC) scheme for back-to-back converter control without a dc-link outer-loop controller. Furthermore, the QC-DMPC is experimentally compared with a conventional proportional-integration (PI) dc-link controller-based DMPC (PI-DMPC) scheme. For the QC-DMPC scheme, the dc-link voltage is directly controlled by a grid-side predictive controller using a dynamic reference generation concept and load-side power estimation. For the PI-DMPC scheme, the dc-link voltage is controlled by an external PI controller. Both schemes are implemented on a field programmable gate array (FPGA)-based platform. Effectiveness of the proposed QC-DMPC is verified by both simulation and experimental data. Moreover, FPGA implementation issues (resource usage and timing information), dc-link control performance, and robustness to parameter variation of the two DMPC schemes are compared in detail. The results emphasize that the QC-DMPC may outperform the PI-DMPC scheme in normal operation but with a slightly higher usage of FPGA resources. However, PI-DMPC scheme is more robust when parameter variations are considered.

Idioma originalEnglish
Número de artículo7024917
Páginas (desde-hasta)662-674
Número de páginas13
PublicaciónIEEE Transactions on Power Electronics
Volumen31
N.º1
DOI
EstadoPublished - 1 ene 2016

Huella dactilar

Model predictive control
Field programmable gate arrays (FPGA)
Controllers
Electric potential
Power converters

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Citar esto

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abstract = "Voltage source back-to-back power converters are widely used in grid-tied applications. This paper presents a quasi-centralized direct model predictive control (QC-DMPC) scheme for back-to-back converter control without a dc-link outer-loop controller. Furthermore, the QC-DMPC is experimentally compared with a conventional proportional-integration (PI) dc-link controller-based DMPC (PI-DMPC) scheme. For the QC-DMPC scheme, the dc-link voltage is directly controlled by a grid-side predictive controller using a dynamic reference generation concept and load-side power estimation. For the PI-DMPC scheme, the dc-link voltage is controlled by an external PI controller. Both schemes are implemented on a field programmable gate array (FPGA)-based platform. Effectiveness of the proposed QC-DMPC is verified by both simulation and experimental data. Moreover, FPGA implementation issues (resource usage and timing information), dc-link control performance, and robustness to parameter variation of the two DMPC schemes are compared in detail. The results emphasize that the QC-DMPC may outperform the PI-DMPC scheme in normal operation but with a slightly higher usage of FPGA resources. However, PI-DMPC scheme is more robust when parameter variations are considered.",
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FPGA-Based Experimental Investigation of a Quasi-Centralized Model Predictive Control for Back-to-Back Converters. / Zhang, Zhenbin; Wang, Fengxiang; Sun, Tongjing; Rodríguez, José; Kennel, Ralph.

En: IEEE Transactions on Power Electronics, Vol. 31, N.º 1, 7024917, 01.01.2016, p. 662-674.

Resultado de la investigación: Article

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AU - Kennel, Ralph

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