Direct flux and current vector control for induction motor drives using model predictive control theory

Odhano, Shafiq; Bojoi, Radu; Formentini, Andrea; Zanchetta, Pericle; Tenconi, Alberto

Abstract

The study presents the direct flux and current vector control of an induction motor (IM) drive, which is a relatively newer and promising control strategy, through the use of model predictive control (MPC) techniques. The results highlight that the fast flux control nature of direct flux control strategy is further enhanced by MPC. Predictive control is applied in two of its variants, namely the finite control set and modulated MPC, and the advantages and limitations of the two are underlined. This work also highlights, through experimental results, the importance of prioritising the flux part of the cost function which is particularly significant in the case of an IM drive. The performance of the MPC-based approach is compared with the proportional-integral controller, which also prioritises the flux control loop, under various operating regions of the drive such as in the flux-weakening regime. Simulations show the performance expected with different control strategies which is then verified through experiments.

Citation

Odhano, S., Bojoi, R., Formentini, A., Zanchetta, P., & Tenconi, A. (2017). Direct flux and current vector control for induction motor drives using model predictive control theory. IET Electric Power Applications, 11(8), 1483-1491. https://doi.org/10.1049/iet-epa.2016.0872

• Journal Article Type: Article
• Acceptance Date: Jun 19, 2017
• Online Publication Date: Jun 21, 2017
• Publication Date: Sep 4, 2017
• Deposit Date: Oct 11, 2017
• Publicly Available Date: Oct 11, 2017
• Journal: IET Electric Power Applications
• Print ISSN: 1751-8660
• Electronic ISSN: 1751-8679
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 8
• Pages: 1483-1491
• DOI: https://doi.org/10.1049/iet-epa.2016.0872
• Keywords: induction motor drives, machine theory, machine vector control, predictive control
• Public URL: https://nottingham-repository.worktribe.com/output/881073
• Publisher URL: http://digital-library.theiet.org/content/journals/10.1049/iet-epa.2016.0872
• Related Public URLs: http://ieeexplore.ieee.org/document/8023940/?arnumber=8023940
• Additional Information: This paper is a postprint of a paper submitted to and accepted for publication in IET Electric Power Applications and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.
• Contract Date: Oct 11, 2017