控制理论(社会学)
电感
计算
瞬态(计算机编程)
定子
模型预测控制
电压
病媒控制
同步电动机
扭矩
计算机科学
航程(航空)
工程类
控制(管理)
感应电动机
算法
物理
人工智能
电气工程
操作系统
热力学
机械工程
航空航天工程
作者
Zixuan Liu,Xiaoyan Huang,Qichao Hu,Zhaokai Li,Ze Jiang,Yelong Yu,Zhuo Chen
标识
DOI:10.1109/tpel.2022.3188761
摘要
This article proposes a modified deadbeat predictive current control (M-DPCC) method to improve the dynamic performance of permanent magnet synchronous motor (PMSM). Classical DPCC only predicts one control cycle of the PMSM, which restricts the dynamic performance since multiple control cycles are required for the transient state under heavy load and rated speed working condition. The proposed M-DPCC extends the single-step prediction to the entire dynamic interval in the transient state, by which the comprehensive optimization on the angle of the stator voltage vector can be implemented. Moreover, M-DPCC performed multi-step deadbeat calculation to keep the computation modest. To verify the effectiveness of the proposed M-DPCC, transient-state performance of PMSM using the M-DPCC method, the modulated model predictive control and classical DPCC are explored under a wide range of working condition. Comparative simulation and experimental results indicate that dynamic performance of the PMSM can be improved, especially under rated speed and heavy load conditions. Besides, the parameter sensitivity to inductance mismatch of the three methods is carried out. The stable operation range of the M-DPCC under inductance mismatch is larger than the other two methods. Moreover, the computation complexity of the three methods were investigated. The M-DPCC acquired less computation time than the modulated model predictive control.
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