A Robust Complex Vector PI Current Controller With Deadbeat Response for PMSM Drives

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2024-10-30 DOI:10.1109/TIE.2024.3482013
Junkai Wen;Xin Yuan;Shuangxia Niu;W. L. Chan
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Abstract

Permanent magnet synchronous motors (PMSMs) require high performance digital current cont rollers to implement high-precision industrial applications. To improve overall performance, including transient, steady-state, robustness performance, this article proposes a robust complex vector proportional–integral (PI) current controller. The framework of the controller is designed in three directions: dynamic response, disturbance rejection, and stability. Moreover, aiming at further eliminating the impact of parameter mismatches on the performance of the controller, a complex vector current estimator is proposed. By adjusting the designed parameters, the controller can not only achieve a deadbeat response, but also possess strong disturbance rejection ability and stability. The accuracy of the current estimator and the effectiveness of the proposed PI controller are verified through experimental results.
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用于 PMSM 驱动器的具有死区响应的鲁棒复杂矢量 PI 电流控制器
永磁同步电机(pmms)需要高性能的数字电流控制辊来实现高精度的工业应用。为了提高整体性能,包括瞬态、稳态和鲁棒性性能,本文提出了一种鲁棒的复向量比例积分(PI)电流控制器。从动态响应、抗扰性和稳定性三个方面设计了控制器的框架。此外,为了进一步消除参数不匹配对控制器性能的影响,提出了一种复杂矢量电流估计器。通过对设计参数的调整,控制器不仅可以实现无差拍响应,而且具有较强的抗扰能力和稳定性。实验结果验证了电流估计器的准确性和PI控制器的有效性。
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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