A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers

Zhou Yunhong; Zhang Aimin; Zhang Hang; Huang Jingjing; Du Yudong; Zhang Lei; Zhang Wei

doi:10.1109/IECON43393.2020.9254979

A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers

Zhou Yunhong
, Zhang Aimin
, Zhang Hang
, Huang Jingjing
, Du Yudong
, Zhang Lei
, Zhang Wei

Faculty of Electronic and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

A model predictive control with online inductance estimator (OIEMPC) for three-phase VIENNA rectifiers is presented in this paper. An OIE adopting the dynamic filtering method and least square algorithm is proposed to further improve system robustness. In this OIE, the VIENNA rectifier pole voltages are obtained by computation utilizing the gate signals of the switching devices, AC current direction and the DC voltage, so that no additional voltage sensors are needed. Compared to the conventional MPC with finite control set (FCS-MPC), the proposed strategy can have better control performance, which effectively improves the robustness of the system. The effectiveness and correctness of the proposed OIEMPC method are demonstrated by the results of Simulink experiments.

Original language	English
Title of host publication	Proceedings - IECON 2020
Subtitle of host publication	46th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
Pages	4607-4611
Number of pages	5
ISBN (Electronic)	9781728154145
DOIs	https://doi.org/10.1109/IECON43393.2020.9254979
State	Published - 18 Oct 2020
Event	46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore Duration: 19 Oct 2020 → 21 Oct 2020

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2020-October

Conference

Conference	46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Country/Territory	Singapore
City	Virtual, Singapore
Period	19/10/20 → 21/10/20

Keywords

VIENNA rectifier
least square algorithm
model predictive control
online inductance estimator

Access to Document

10.1109/IECON43393.2020.9254979

Cite this

Yunhong, Z., Aimin, Z., Hang, Z., Jingjing, H., Yudong, D., Lei, Z., & Wei, Z. (2020). A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers. In Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society (pp. 4607-4611). Article 9254979 (IECON Proceedings (Industrial Electronics Conference); Vol. 2020-October). IEEE Computer Society. https://doi.org/10.1109/IECON43393.2020.9254979

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title = "A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers",

abstract = "A model predictive control with online inductance estimator (OIEMPC) for three-phase VIENNA rectifiers is presented in this paper. An OIE adopting the dynamic filtering method and least square algorithm is proposed to further improve system robustness. In this OIE, the VIENNA rectifier pole voltages are obtained by computation utilizing the gate signals of the switching devices, AC current direction and the DC voltage, so that no additional voltage sensors are needed. Compared to the conventional MPC with finite control set (FCS-MPC), the proposed strategy can have better control performance, which effectively improves the robustness of the system. The effectiveness and correctness of the proposed OIEMPC method are demonstrated by the results of Simulink experiments.",

keywords = "VIENNA rectifier, least square algorithm, model predictive control, online inductance estimator",

author = "Zhou Yunhong and Zhang Aimin and Zhang Hang and Huang Jingjing and Du Yudong and Zhang Lei and Zhang Wei",

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doi = "10.1109/IECON43393.2020.9254979",

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Yunhong, Z, Aimin, Z, Hang, Z, Jingjing, H, Yudong, D, Lei, Z & Wei, Z 2020, A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers. in Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society., 9254979, IECON Proceedings (Industrial Electronics Conference), vol. 2020-October, IEEE Computer Society, pp. 4607-4611, 46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020, Virtual, Singapore, Singapore, 19/10/20. https://doi.org/10.1109/IECON43393.2020.9254979

A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers. / Yunhong, Zhou; Aimin, Zhang; Hang, Zhang et al.
Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2020. p. 4607-4611 9254979 (IECON Proceedings (Industrial Electronics Conference); Vol. 2020-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers

AU - Yunhong, Zhou

AU - Aimin, Zhang

AU - Hang, Zhang

AU - Jingjing, Huang

AU - Yudong, Du

AU - Lei, Zhang

AU - Wei, Zhang

PY - 2020/10/18

Y1 - 2020/10/18

N2 - A model predictive control with online inductance estimator (OIEMPC) for three-phase VIENNA rectifiers is presented in this paper. An OIE adopting the dynamic filtering method and least square algorithm is proposed to further improve system robustness. In this OIE, the VIENNA rectifier pole voltages are obtained by computation utilizing the gate signals of the switching devices, AC current direction and the DC voltage, so that no additional voltage sensors are needed. Compared to the conventional MPC with finite control set (FCS-MPC), the proposed strategy can have better control performance, which effectively improves the robustness of the system. The effectiveness and correctness of the proposed OIEMPC method are demonstrated by the results of Simulink experiments.

AB - A model predictive control with online inductance estimator (OIEMPC) for three-phase VIENNA rectifiers is presented in this paper. An OIE adopting the dynamic filtering method and least square algorithm is proposed to further improve system robustness. In this OIE, the VIENNA rectifier pole voltages are obtained by computation utilizing the gate signals of the switching devices, AC current direction and the DC voltage, so that no additional voltage sensors are needed. Compared to the conventional MPC with finite control set (FCS-MPC), the proposed strategy can have better control performance, which effectively improves the robustness of the system. The effectiveness and correctness of the proposed OIEMPC method are demonstrated by the results of Simulink experiments.

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KW - least square algorithm

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KW - online inductance estimator

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Yunhong Z, Aimin Z, Hang Z, Jingjing H, Yudong D, Lei Z et al. A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers. In Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society. 2020. p. 4607-4611. 9254979. (IECON Proceedings (Industrial Electronics Conference)). doi: 10.1109/IECON43393.2020.9254979

A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers

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Keywords

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