LAPSE:2023.30384
Published Article
LAPSE:2023.30384
Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems
Ibrahim Farouk Bouguenna, Ahmed Tahour, Ralph Kennel, Mohamed Abdelrahem
April 14, 2023
Abstract
This article presents a multiple-vector finite-control-set model predictive control (MV-FCS-MPC) scheme with fuzzy logic for permanent-magnet synchronous motors (PMSMs) used in electric drive systems. The proposed technique is based on discrete space vector modulation (DSVM). The converter’s real voltage vectors are utilized along with new virtual voltage vectors to form switching sequences for each sampling period in order to improve the steady-state performance. Furthermore, to obtain the reference voltage vector (VV) directly from the reference current and to reduce the calculation load of the proposed MV-FCS-MPC technique, a deadbeat function (DB) is added. Subsequently, the best real or virtual voltage vector to be applied in the next sampling instant is selected based on a certain cost function. Moreover, a fuzzy logic controller is employed in the outer loop for controlling the speed of the rotor. Accordingly, the dynamic response of the speed is improved and the difficulty of the proportional-integral (PI) controller tuning is avoided. The response of the suggested technique is verified by simulation results and compared with that of the conventional FCS-MPC.
Keywords
deadbeat function, fuzzy logic controller, Model Predictive Control, multiple-vector
Suggested Citation
Bouguenna IF, Tahour A, Kennel R, Abdelrahem M. Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems. (2023). LAPSE:2023.30384
Author Affiliations
Bouguenna IF: Institute for Electrical Engineering, University of Mascara, Mascara 29000, Algeria [ORCID]
Tahour A: Higher School of Applied Sciences, Tlemcen 13000, Algeria
Kennel R: Institute for Electrical Drive Systems and Power Electronics (EAL), Technische Universität München (TUM), 80333 Munich, Germany
Abdelrahem M: Institute for Electrical Drive Systems and Power Electronics (EAL), Technische Universität München (TUM), 80333 Munich, Germany; Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut 71516, Egypt [ORCID]
Journal Name
Energies
Volume
14
Issue
6
First Page
1727
Year
2021
Publication Date
2021-03-20
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14061727, Publication Type: Journal Article
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LAPSE:2023.30384
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https://doi.org/10.3390/en14061727
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