Current disturbance compensation of continuous model predictive control scheme for PMSMs

IF 6.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions Pub Date : 2024-12-01 DOI:10.1016/j.isatra.2024.10.007

Pan Luo, Sai Zhang, Anwen Shen, Xin Luo, Qipeng Tang

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引用次数: 0

Abstract

During the operation of a permanent magnet synchronous motor, limitations imposed by digital chips inevitably result in certain delays. Additionally, external environmental factors introduce variations in motor parameters. This study aims to comprehensively analyze these issues. Firstly, the control delay and disturbances caused by motor parameter changes are transformed into current disturbances using a uniform approach. Secondly, various sliding mode model predictive controllers are designed to effectively suppress the current disturbances arising from aforementioned reasons. Moreover, considering controller implementation aspects, this paper thoroughly discusses the influence of core controller parameters on current disturbances and their adaptability toward different parameter mismatches. Furthermore, extensive examination is conducted on global stability conditions for controller realization. Finally, experimental results validate that the proposed methods successfully optimize current disturbances originating from aforementioned causes.

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用于 PMSM 的连续模型预测控制方案的电流干扰补偿。

在永磁同步电机的运行过程中，数字芯片的限制不可避免地会导致某些延迟。此外，外部环境因素也会导致电机参数发生变化。本研究旨在全面分析这些问题。首先，采用统一方法将电机参数变化引起的控制延迟和干扰转化为电流干扰。其次，设计了各种滑模模型预测控制器，以有效抑制上述原因引起的电流干扰。此外，考虑到控制器实施方面的问题，本文深入讨论了核心控制器参数对电流干扰的影响及其对不同参数失配的适应性。此外，本文还对实现控制器的全局稳定性条件进行了广泛研究。最后，实验结果验证了所提出的方法能成功优化由上述原因引起的电流干扰。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ISA transactions 工程技术-工程：综合

CiteScore

11.70

自引率

12.30%

发文量

824

审稿时长

4.4 months

期刊介绍： ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.