Dynamic decoupling control for radial position of bearingless induction motor based on neural networks inverse system

2009 IEEE 6th International Power Electronics and Motion Control Conference Pub Date : 2009-05-17 DOI:10.1109/IPEMC.2009.5157457

Xiaodong Sun, Huangqiu Zhu, Zhang Tao

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Abstract

The operation principle of bearingless induction motor was introduced, and then the mathematical equation of the radial force model for the bearingless induction motor with conventional 4-pole stator windings and additional 2-pole windings was transformed. A decoupling control method named as neural network inverse system (NNIS) was presented for the radial suspending model of bearingless induction motor. Aimed at the nonlinear and strongly coupled characteristics, the model is analyzed with reversibility and proved to be reversible. The multi variable, strongly coupled, nonlinear system was dynamic decoupled into two linear displacement subsystems by connecting a NNIS before the bearingless induction motor. Then the two decoupled linear subsystems were synthesized under the help of lineal closed-loop controllers. The simulation test results show that independent control on two degrees of freedom of radial position for the bearingless induction motor can be realized through NNIS method and the dynamic and static performance of the closed loop system designed is satisfactory.

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基于神经网络逆系统的无轴承异步电动机径向位置动态解耦控制

介绍了无轴承异步电动机的工作原理，对常规4极定子绕组加2极定子绕组的无轴承异步电动机径向力模型的数学方程进行了转换。针对无轴承异步电动机径向悬浮模型，提出了一种神经网络逆系统解耦控制方法。针对系统的非线性和强耦合特性，对模型进行可逆性分析，证明了模型的可逆性。通过在无轴承感应电机前连接NNIS，将多变量强耦合非线性系统动态解耦为两个线性位移子系统。然后在线性闭环控制器的帮助下对两个解耦的线性子系统进行综合。仿真试验结果表明，采用NNIS方法可以实现对无轴承异步电动机两自由度径向位置的独立控制，所设计的闭环系统的动静态性能令人满意。

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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2009 IEEE 6th International Power Electronics and Motion Control Conference

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