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A Modulated Model Predictive Control Scheme for the Brushless Doubly Fed Induction Machine

Li, Xuan; Peng, Tao; Dan, Hanbing; Zhang, Guanguan; Tang, Weiyi; Jin, Weiyu; Wheeler, Patrick; Rivera, Marco

Authors

Xuan Li

Tao Peng

Hanbing Dan

Guanguan Zhang

Weiyi Tang

Weiyu Jin

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PATRICK WHEELER pat.wheeler@nottingham.ac.uk
Professor of Power Electronic Systems

Marco Rivera



Abstract

© 2013 IEEE. Brushless doubly fed induction machines (BDFIMs) feature some important advantages, such as high reliability and low maintenance cost, over alternative solutions for brushless machine applications. This paper proposes a modulated model predictive control (MPC) algorithm for BDFIMs, which achieves a fixed switching frequency and superior system performance. An improvement of power quality is shown in this paper when compared to the conventional finite-control set-MPC. This paper examines the design and implementation of the modulation technique as well as presenting the simulation and experimental results to verify the technique's operation.

Citation

Li, X., Peng, T., Dan, H., Zhang, G., Tang, W., Jin, W., …Rivera, M. (2018). A Modulated Model Predictive Control Scheme for the Brushless Doubly Fed Induction Machine. IEEE Journal of Emerging and Selected Topics in Power Electronics, 6(4), 1681-1691. https://doi.org/10.1109/JESTPE.2018.2865668

Journal Article Type Article
Acceptance Date Aug 11, 2018
Online Publication Date Aug 16, 2018
Publication Date 2018-12
Deposit Date Oct 1, 2018
Publicly Available Date Oct 2, 2018
Journal IEEE Journal of Emerging and Selected Topics in Power Electronics
Print ISSN 2168-6777
Electronic ISSN 2168-6785
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 6
Issue 4
Pages 1681-1691
DOI https://doi.org/10.1109/JESTPE.2018.2865668
Keywords Brushless doubly-fed induction machine, modulated model predictive control
Public URL https://nottingham-repository.worktribe.com/output/1141528
Publisher URL https://ieeexplore.ieee.org/document/8438501
Additional Information © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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