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A study of sensorless vector control of IM using neural network luenberger observer

机译:我国神经网络无传感器矢量控制研究Luenberger观察者

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After the development of electronic components, the elimination of the sensors has become a necessary subject to get good results in the field of speed control, because of the price of the sensors, the strenuous choice of its position and the disturbance of measurement which affects the robustness of control. The luenberger observer showed to be one of the most excellent methods suggested by the researchers; this is due to the best performance, it offers in terms of stability, reliability and less counting effort. In this article, a study of luenberger observer based on neural network-based was discussed. This artificial intelligence method makes it possible to decrease the error of estimated speed for IRFOC control of the induction motor. Simulation results are obtained to show the robustness and stability of the system.
机译:在开发电子元器件后,消除传感器已成为在速度控制领域获得良好的必要主题,因为传感器的价格,其位置的剧烈选择和影响的测量障碍控制的鲁棒性。 Luenberger Observer显示是研究人员建议的最优秀方法之一;这是由于最佳性能,它在稳定性,可靠性和较少的计数努力方面提供。在本文中,讨论了基于神经网络的Luenberger观察者的研究。这种人工智能方法可以降低对感应电动机的IRFOC控制的估计速度误差。获得仿真结果以显示系统的鲁棒性和稳定性。

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