控制理论(社会学)
稳健性(进化)
模型预测控制
超调(微波通信)
计算机科学
观察员(物理)
扭矩
控制工程
工程类
控制(管理)
热力学
基因
物理
人工智能
电信
化学
量子力学
生物化学
作者
Yongchang Zhang,Jialin Jin,Lan–Lan Huang
出处
期刊:IEEE Transactions on Industrial Electronics
[Institute of Electrical and Electronics Engineers]
日期:2020-02-05
卷期号:68 (2): 993-1003
被引量:293
标识
DOI:10.1109/tie.2020.2970660
摘要
Conventional model predictive current control (MPCC) is a powerful control strategy for three-phase inverters that has the advantages of simple concept, quick response, easy implementation, and good performance. However, MPCC is sensitive to machine parameter variation, and the performance degrades substantially if a mismatch exists between the model parameters and real machine parameters. Model-free predictive current control (MFPCC) based on an ultralocal model, which uses only the input and output of the system without considering any motor parameters, has been proposed to solve this problem in this article. Since parameters are not required, the robustness of the control system is improved. However, conventional MFPCC based on an ultralocal model uses many control parameters, which increases the tuning work. Furthermore, the control performance is not ideal at low sampling frequency. This article proposes an improved MFPCC based on the extended state observer of PMSM drives that does not require motor parameters and needs less tuning work and lower computational time while achieving the better performance in terms of current harmonics, tracking error, and dynamic overshoot. The proposed method is compared to conventional MPCC and MFPCC, and the effectiveness is confirmed by the simulation and experimental results.
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