Displacement Sensorless Operation Control of Bearingless Permanent Magnet Synchronous Motor Based on BP Neural Network Left Inverse

被引：0
|
作者：
Zhu H. [1 ]
Yan L. [1 ]
Diao X. [1 ]
机构：
[1] School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu Province
来源：
| 1600年 / Chinese Society for Electrical Engineering卷 / 40期
基金：
中国国家自然科学基金;
关键词：
Bearingless permanent magnet synchronous motor; Displacement sensorless; Flux observer; Left inverse; Neural network;
D O I：
10.13334/j.0258-8013.pcsee.190705
中图分类号：
学科分类号：
摘要：
In order to solve the problems of large volume, high cost and low reliability in the use of mechanical displacement sensors for bearingless permanent magnet synchronous motor (BPMSM), a rotor radial displacement observation method based on BP neural network was proposed. Firstly, the subsystem of radial displacement and suspension windings flux linkage was established, and its left reversibility was proved. The left inverse model of the subsystem was constructed by using the fitting ability of BP neural network, and the observation of radial displacements was realized. Secondly, in order to improve the accuracy of displacement observation, the second order generalized integrator was used to observe the flux linkage. Then, on the basis of displacement observation and flux linkage observation, based on the direct torque and direct suspension force control strategy, the displacement sensorless control system of the BPMSM was constructed. Finally, the simulation and experimental research were carried out. The results show that the method can effectively observe the radial displacements of the rotor, and its accuracy and feasibility were verified. © 2020 Chin. Soc. for Elec. Eng.
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收藏
页码：3673 / 3680
页数：7
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