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Modeling of X-Y macro-positioning stage based on non-smooth neural networks

机译:基于非光滑神经网络的X-Y宏定位平台建模

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In this paper, a novel neutral-network-based model is proposed to describe an X-Y macro-positioning stage. As the friction exists in the stage, the stage shows some complex behavior due to the non-smooth characteristic of the friction. In order to describe the non-smooth behavior of the stage, in this model, a non-smooth active function is proposed to construct the hidden neurons. Then, a training algorithm cooperated with the generalized gradient technique is developed to train the proposed neural network. Finally, the experimental results are presented to illustrate the performance of the proposed method.
机译:在本文中,提出了一种新颖的基于神经网络的模型来描述X-Y宏定位阶段。由于阶段中存在摩擦,由于摩擦的非平滑特性,阶段显示出一些复杂的行为。为了描述该阶段的非平滑行为,在该模型中,提出了一种非平滑活动函数来构造隐藏神经元。然后,开发了一种与广义梯度技术相结合的训练算法来训练所提出的神经网络。最后,给出了实验结果以说明该方法的性能。

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