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CMAC neural network application for induction motor drives

机译:CMAC神经网络在感应电动机驱动中的应用

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This article presents a newly developed speed-sensorless induction motor drive using cerebellar-model-articulation-controller (CMAC). The gradient-type learning algorithm is used to train the CMAC neural network online in order to provide a real-time adaptive identification of the motor speed. The CMAC is then viewed as a speed estimator that produces the estimated speed to the speed control loop that accomplishes the speed-sensorless vector control drive. From the experimental results, the proposed CMAC speed estimator forces the estimated speed to follow the actual motor speed precisely. The article describes both the theoretical analysis as well as the simulation results to verify the effectiveness of the proposed method.
机译:本文介绍了一种新开发的使用小脑模型关节运动控制器(CMAC)的无速度传感器感应电动机驱动器。梯度类型学习算法用于在线训练CMAC神经网络,以便提供电动机速度的实时自适应识别。然后,将CMAC视为速度估算器,它将估算出的速度提供给完成无速度传感器矢量控制驱动的速度控制环。从实验结果来看,提出的CMAC速度估算器会强制估算速度精确地遵循实际电动机速度。本文介绍了理论分析和仿真结果,以验证所提方法的有效性。

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