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Instantaneous Torque Control of Translational Meshing Motors Based on Neural Network

机译:基于神经网络的翻译啮合电动机瞬时扭矩控制

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An adaptive neural network control of a novel type of translational meshing motor with model uncertainties is considered. Owing to its nonlinear characteristic, a model reference control system which consists of two neural networks is used. The torque model is identified based on BP neural network, and then a RBF neural network works as the controller. The model reference control system is trained for the optimizing parameters and research of control strategy. The description of the control system and training procedure of the two neural networks are given. The test results obtained for a torque control scheme suitable for the control of the motor are also presented to verify the effectiveness of the proposed nonlinear control scheme. It has been found that the neural network control system is able to work reliably.
机译:考虑了一种具有模型不确定性的新型翻译啮合电动机的自适应神经网络控制。由于其非线性特性,使用由两个神经网络组成的模型参考控制系统。基于BP神经网络识别扭矩模型,然后RBF神经网络用作控制器。模型参考控制系统接受了优化参数和控制策略的研究。给出了对两个神经网络的控制系统和训练过程的描述。还提出了适用于控制电动机的扭矩控制方案获得的测试结果以验证所提出的非线性控制方案的有效性。已经发现神经网络控制系统能够可靠地工作。

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