Composite Multi-Vector Model Predictive Control for Permanent Magnet Synchronous Motor
被引:0
作者:
Gao, Lin
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R ChinaAnhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R China
Gao, Lin
[1
]
Pan, Tianhong
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R ChinaAnhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R China
Pan, Tianhong
[1
]
机构:
[1] Anhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R China
来源:
2023 IEEE 12TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE, DDCLS
|
2023年
关键词:
Model predictive control;
Multi-vector;
Current harmonics;
DRIVES;
D O I:
10.1109/DDCLS58216.2023.10167075
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
Model Predictive Control (MPC) has been widely used in the permanent magnet synchronous motor. However, in the finite control set MPC, only one voltage vector is applied, which leads to high current harmonics and torque fluctuations. Meanwhile, three-vector MPC inevitably increases the switching frequency of inverter. In this article, a multi-vector switching control approach is established. Based on the location information of the created reference voltage vector, the relevant control technique is implemented. The proposed control method with single-vector, two-vector and three-vector composite modes of action is designed to achieve low switching frequency with excellent steady-state performance. The proposed method's effectiveness is confirmed by the experimental results.