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Lookup NU author(s): Dr Shafiq OdhanoORCiD
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE, 2019.
For re-use rights please refer to the publisher's terms and conditions.
© 2019 IEEE. The paper deals with a newly developed sequential model predictive control strategy for the high-performance control of electric drives. The sequential nature of cost function evaluation allows to eliminate weighting factors whose tuning is not straightforward. In the first cost function evaluation, torque (or flux) error is minimized and, the second evaluation minimizes the flux (or torque) error. The first optimization generates two optimal voltage vectors that give minimum error for the controlled variable and the second optimization tests only the selected two vectors to find the global optimal. In this paper, a detailed analysis of the sequential MPC is carried out with a focus on the inversion of sequence of optimization with respect to the original algorithm. The paper also analyses the effect of selecting more than two vectors from the first evaluation and explains to the reader why some numbers of selected vectors produce flux and torque distortions while others do not control flux and torque at all.
Author(s): Vodola V, Odhano S, Norambuena M, Garcia C, Vaschetto S, Zanchetta P, Rodriguez J, Bojoi R
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: IEEE Energy Conversion Congress and Exposition (ECCE 2019)
Year of Conference: 2019
Pages: 6595-6600
Online publication date: 28/11/2019
Acceptance date: 02/04/2018
Date deposited: 30/03/2020
ISSN: 2329-3748
Publisher: IEEE
URL: https://doi.org/10.1109/ECCE.2019.8912708
DOI: 10.1109/ECCE.2019.8912708
Library holdings: Search Newcastle University Library for this item
ISBN: 9781728103952