A modulated model predictive control scheme for the brushless doubly-fed induction machine

Li, Xuan; Peng, Tao; Dan, Hanbing; Zhang, Guanguan; Tang, Weiyi; Wheeler, Pat

Abstract

This paper proposes a modulated model predictive control (MMPC) algorithm for a brushless double-fed induction machine. The Brushless Doubly-Fed Induction Machine has some important advantages over alternative solutions for brushless machine applications. The proposed modulation technique achieves a fixed switching frequency, which gives good system performance. The paper examines the design and implementation of the modulation technique and shows the comparison of finite control set-model predictive control (FCS-MPC) and MMPC. Simulation results verify the operation of the proposed modulation technique.

Citation

Li, X., Peng, T., Dan, H., Zhang, G., Tang, W., & Wheeler, P. (2017). A modulated model predictive control scheme for the brushless doubly-fed induction machine. In 2017 IEEE Energy Conversion Congress and Exposition (ECCE) (1338-1342). https://doi.org/10.1109/ECCE.2017.8095945

• Conference Name: IEEE Energy Conversion Congress and Exposition (ECCE) 2017
• Conference Location: Cincinnatti, OH, USA
• Start Date: Oct 1, 2017
• End Date: Oct 5, 2017
• Acceptance Date: May 1, 2017
• Online Publication Date: Nov 7, 2017
• Publication Date: Oct 2, 2017
• Deposit Date: Mar 21, 2018
• Publicly Available Date: Mar 21, 2018
• Peer Reviewed: Peer Reviewed
• Pages: 1338-1342
• Book Title: 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
• ISBN: 978-1-5090-2999-0
• DOI: https://doi.org/10.1109/ECCE.2017.8095945
• Keywords: Brushless doubly-fed induction machine; Modulated model predictive control
• Public URL: https://nottingham-repository.worktribe.com/output/886175
• Publisher URL: http://ieeexplore.ieee.org/document/8095945/
• Related Public URLs: http://www.ieee-ecce.org/2017/
• Additional Information: © 2017 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.