A Review on Weighting Factor Design of Finite Control Set Model Predictive Control Strategies for AC Electric Drives

模型预测控制 加权 控制(管理) 控制理论(社会学) 集合(抽象数据类型) 计算机科学 因子(编程语言) 控制工程 工程类 物理 人工智能 声学 程序设计语言
作者
Emrah Zerdali,Marco Rivera,Patrick Wheeler
出处
期刊:IEEE Transactions on Power Electronics [Institute of Electrical and Electronics Engineers]
卷期号:39 (8): 9967-9981 被引量:9
标识
DOI:10.1109/tpel.2024.3370550
摘要

Model predictive control has been widely applied to AC electric drives over the last decade. Despite the proposed solutions, researchers are still seeking to find more effective solutions for weighting factor design, parameter dependency, current/torque harmonics, variable switching frequency, and computational complexity. This paper presents a comprehensive review of the weighting factor design techniques for finite control set model predictive control strategies for AC electric drives. First, the paper introduces the conventional model predictive control techniques for electric drives over permanent magnet synchronous motors. Second, weighting factor design methods are discussed under two main headings: weighting factor selection and weighting factor elimination methods. Third, the ongoing challenges and future trends are addressed by considering the current literature. Based on this review, it is obvious that each weighting factor design method still has problems that await more effective solutions. Finally, this paper reviews various weighting factor design methods for AC electric drives, reveals the advantages and disadvantages of existing methods in terms of control performance, flexibility, design complexity, and computational complexity, and highlights future trends.
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