控制理论(社会学)
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模型预测控制
稳健性(进化)
逆变器
电容器
直流电动机
电压
计算机科学
电动机驱动
工程类
控制(管理)
电气工程
人工智能
基因
机械工程
化学
程序设计语言
生物化学
作者
Haitao Yang,Min Li,Yongchang Zhang,Aoyang Xu
标识
DOI:10.1109/tie.2023.3279558
摘要
The conventional finite-control-set model-predictive control (FCS-MPC) suffers from poor robustness against model mismatches. This article presents an improved FCS-MPC with a reconstructed mathematical model to predict current variations without using a lookup table (LUT) or motor parameters. The model coefficients and current variations related to different voltage vectors can be updated during each control period. As a result, the prediction error is significantly reduced at low switching frequency when compared to the prior LUT-based model-free predictive current control. In addition, the tracking accuracy of the proposed method at high speeds is improved due to the elimination of approximation error. Furthermore, a simple scheme is developed to suppress neutral-point potential drift without the knowledge of the dc-bus capacitor. Simulation and experimental tests, along with comparisons with prior arts carried out on a three-level inverter-fed surface-mounted permanent magnet synchronous motor drive, confirm the superiority of the proposed method.
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