Improved Deadbeat Algorithm‐Based Sequential Model Predictive Control Strategy for QZSI‐PMSM System

The conventional model predictive control (MPC) for the quasi‐Z‐source inverter–permanent magnet synchronous motor (QZSI‐PMSM) system suffers from conflicts between the modulation coefficients of both sides and many weighting coefficients in the cost function when considering all the control variabl...

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Bibliographic Details
Published in:Journal of engineering (Stevenage, England) Vol. 2025; no. 1
Main Authors: Cheng, Zhun, Cao, Kun, Liu, Chenhui, Liu, Ziying, Luo, Bing, Zhang, Yang
Format: Journal Article
Language:English
Published: 01.01.2025
ISSN:2051-3305, 2051-3305
Online Access:Get full text
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Summary:The conventional model predictive control (MPC) for the quasi‐Z‐source inverter–permanent magnet synchronous motor (QZSI‐PMSM) system suffers from conflicts between the modulation coefficients of both sides and many weighting coefficients in the cost function when considering all the control variables. Aiming at the above issues, an improved deadbeat algorithm‐based sequential MPC (IDA‐SMPC) strategy is proposed in this paper. In the proposed strategy, the drive pulses of the inverter are generated by the alternating effects of straight‐through (ST) voltage vectors (VVs) and non‐straight‐through (NST) VVs in one control period. To begin with, the respective action time of different VVs is obtained separately according to the improved deadbeat algorithm to realize accurate tracking of control targets. Then, the action time is corrected to avoid the possible conflict of the modulation coefficients between the QZSI‐side and the PMSM‐side. In addition, the error of the DC bus current is chosen as the second cost function. This enables the system to operate stably under all operating conditions by considering all control variables, while all weighting factors in the cost function are eliminated. Finally, the experimental verification is tested on the RT‐LAB experimental platform, which proves the correctness and effectiveness of the proposed strategy.
ISSN:2051-3305
2051-3305
DOI:10.1049/tje2.70075