Sensorless Control of Permanent Magnet Synchronous Motor Based on Double- Cost-Function Finite-Position-Set Phase-Locked Loop

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2024-09-04 DOI:10.1109/TIE.2024.3417969
Xiang Wu;Jia Li;Shuo Chen;Zhixun Ma;Yaofei Han;Xiao Zhang
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Abstract

Finite-position-set phase-locked loop (FPS-PLL) is a research hotspot in the sensorless control of permanent magnet synchronous motor (PMSM) due to its excellent dynamic response and no parameters tuning, but it takes the high computational burden and may suffer from a rotor position error of 180°. To solve the above problems, a double-cost-function FPS-PLL (DCF-FPS-PLL) is proposed in this article, where two different cost functions are defined to decide the iteration direction and guarantee the convergence of the Newton iteration method. The estimation accuracy of the rotor position is theoretically 4.73e-6 rad for the DCF-FPS-PLL without considering the error caused by the observer while only three iterations are needed, which reduces the large amount of computation without sacrificing the accuracy. The experimental results verify the advantages of the DCF-FPS-PLL.
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基于双成本函数有限位置集锁相环的永磁同步电机无传感器控制
有限位置集锁相环(FPS-PLL)具有动态响应好、无需参数整定等优点,是永磁同步电机无传感器控制的研究热点,但其计算量大,转子位置误差达180°。针对上述问题,本文提出了一种双代价函数FPS-PLL (DCF-FPS-PLL),通过定义两个不同的代价函数来确定迭代方向,保证牛顿迭代法的收敛性。在不考虑观测器误差的情况下,DCF-FPS-PLL的转子位置估计精度理论上为4.73e-6 rad,且只需要三次迭代,在不牺牲精度的情况下减少了大量的计算量。实验结果验证了DCF-FPS-PLL的优越性。
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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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