A Model Predictive Current Control Based on Adaline Neural Network for PMSM

被引:3
|
作者
Li, Hongfeng [1 ]
Liu, Zhengyu [2 ]
Shao, Jianyu [1 ]
机构
[1] Tianjin Univ, Sch Elect & Informat Engn, Tianjin, Peoples R China
[2] Beijing Inst Mech Equipment, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Model predictive current control; Parameter robustness; Permanent magnet synchronous motor;
D O I
10.1007/s42835-022-01324-8
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The parameter mismatch seriously affects the control performance of the model predictive current control (MPCC). Aiming at improving the parameter robustness of MPCC, a MPCC method based on Adaline neural network for permanent magnet synchronous motor (PMSM) is established. First, the parameters sensitivity analysis of PMSM incremental current predic-tion model is carried out that eliminates effects of rotor flux linkage mismatch and resistance mismatch. Therefore, a new incremental current prediction model is built, which does not require rotor flux and resistance parameters. Second, based on the above model, Adaline neural network strategy is introduced to identify the inductance parameters which has a variable momentum to improve accuracy. Then, the strategy proposed in this paper has strong robustness to parameter mismatch. Finally, experiment results verify that the proposed method can effectively improve the parameter robustness.
引用
收藏
页码:953 / 960
页数:8
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