D-Q轴电压纹波最小化矢量控制驱动器使用Type-2 NFS控制器

G. Sukumar, G. Srinivas
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引用次数: 1

摘要

传统的比例积分(PI)控制器需要额外的滤波器来减小电压纹波,并且这些控制器还存在调谐问题。传统PI控制器由于工作点的变化而产生非线性输出。针对上述问题,本文提出了采用间接矢量控制方法的2型神经模糊系统(T2NFS)来减小异步电动机的电压纹波。与传统的比例积分(PI)控制器相比,T2NFS控制器的性能降低了感应电机的电压纹波,无需任何额外的滤波器,并且消除了调谐问题。其中,电流参考值和电流的原始值被馈送到基于T2NFS的控制器,并根据获得的值对控制器进行训练。采用T2NFS控制器对间接矢量控制异步电动机在不同工况下的性能进行了仿真,并与PI控制器进行了比较。实验结果在d空间1104上得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
D-Q axis voltage ripple minimization of vector control drive using Type-2 NFS controller
The voltage ripple is reduced by using conventional proportional integral (PI) controllers require additional filter, and also occurs tuning problem with these controllers. Due to the operating point changes in conventional PI controllers get a nonlinearity output. To overcome above problem, this paper presents Type-2 Neuro fuzzy system (T2NFS) to reduce the voltage ripple in the induction motor by using indirect vector control method. The T2NFS controller performance as compared with conventional proportional integral (PI) controller, voltage ripple reduced in the induction motor without any additional filter and tuning problem is eliminated. In this, the current reference values and original values of current are fed to the T2NFS based controllers and the controller is trained based on the obtained values. The performance of induction motor with indirect vector control method by using T2NFS controllers has been simulated at different operation regions and compared results with PI controllers. The results are experimentally verified with d-space 1104.
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