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首页> 外文期刊>International Journal of Power Electronics and Drive Systems >RNN Based Rotor Flux and Speed Estimation of Induction Motor
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RNN Based Rotor Flux and Speed Estimation of Induction Motor

机译：基于RNN的感应电动机转子磁通和转速估计。

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Speed control of induction motor can be obtained by closed loop system which require speed sensor. Speed sensor system is less effective for wide plant system, because the sensor location is too far from the main control system and measurement result is less accurate. This paper presents the development of speed sensorless field oriented control (FOC) of induction motor by using the rotor flux and speed observers. The observers only required the stator voltage and current of induction motor to obtain the rotor flux and speed estimation. The observers based on recurrent neural network (RNN) methods are implemented. Finally, the effectiveness of the proposed method is verified by simulation. Simulation results show that RNN observer can produce well the rotor flux and speed estimation. MSE values of the rotor flux estimation are between 0.000087 and 0.000264, whereas MSE values of the speed estimation are between 43.0552 and 156.0798. Keywords: field oriented control, induction motor, observer, and recurrent neural network.
机译：感应电动机的速度控制可以通过需要速度传感器的闭环系统来实现。速度传感器系统对于大型工厂系统不太有效，因为传感器位置与主控制系统相距太远，并且测量结果的准确性较低。本文介绍了使用转子磁通和速度观测器的感应电动机无速度传感器磁场定向控制（FOC）的发展。观察者只需要感应电动机的定子电压和电流来获得转子磁通和速度估计。实现了基于递归神经网络（RNN）方法的观察者。最后，通过仿真验证了所提方法的有效性。仿真结果表明，RNN观测器能够很好地产生转子磁链和速度估计。转子磁通估计的MSE值在0.000087和0.000264之间，而速度估计的MSE值在43.0552和156.0798之间。关键字：磁场定向控制，感应电动机，观测器和递归神经网络。

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