Dimension-Reduced Direct Speed Control Based on Line-Constrained Explicit Model Predictive Control for IPMSM

This article presents a dimension-reduced, line-constrained explicit model predictive direct speed control (DRLC-EPDSC) strategy for interior permanent magnet synchronous motor (IPMSM). Conventional explicit model predictive control algorithms suffer from challenges such as high memory usage and long execution times. When applied to direct speed control in a noncascaded structure, the large system dimensionality reduces execution efficiency, complicating deployment on low-cost devices. To address these limitations, the proposed algorithm improves execution efficiency by cutting system dimensionality by more than half compared to traditional methods. Additionally, the improved algorithm contains only a single parameter, thereby avoiding the issues associated with parameter optimization. Experimental results validate the effectiveness of the proposed strategy.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industrial Electronics
Published
2025-06-18
DOI
https://doi.org/10.1109/tie.2025.3574541
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dimension-Reduced Direct Speed Control Based on Line-Constrained Explicit Model Predictive Control for IPMSM

Guijie Yang, Jianyong Su, Han Wang, Pan Li
IEEE Transactions on Industrial Electronics
Industrial Technology and Control Systems
article

Dimension-Reduced Direct Speed Control Based on Line-Constrained Explicit Model Predictive Control for IPMSM

Guijie Yang, Jianyong Su, Han Wang, Pan Li
article en

Abstract

This article presents a dimension-reduced, line-constrained explicit model predictive direct speed control (DRLC-EPDSC) strategy for interior permanent magnet synchronous motor (IPMSM). Conventional explicit model predictive control algorithms suffer from challenges such as high memory usage and long execution times. When applied to direct speed control in a noncascaded structure, the large system dimensionality reduces execution efficiency, complicating deployment on low-cost devices. To address these limitations, the proposed algorithm improves execution efficiency by cutting system dimensionality by more than half compared to traditional methods. Additionally, the improved algorithm contains only a single parameter, thereby avoiding the issues associated with parameter optimization. Experimental results validate the effectiveness of the proposed strategy.

IEEE Transactions on Industrial ElectronicsVol. 72(12)
Harbin University (CN), Harbin Institute of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 85%
Industrial Technology and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.