基于NARX(非线性自回归外生)结构的人工神经网络方法对翻页折页机的辨识

Y. A. Prabowo, W. Pambudi, I. R. Imaduddin
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引用次数: 1

摘要

折叠机是对生产时间效率有要求的中小型洗衣行业所需要的工具。翻转夹是该工具的主要部件,它的作用是通过移动来折叠衣服,形成一定的偏转角度,运动过程由控制器控制。系统建模过程是研究系统特性的第一步。在动态系统中,线性建模的形式被认为难以获得代表实际物理模型的模型。选择非线性自回归外生模型(NARX)的结构来获得系统的动态特性。一种利用人工神经网络(ANN)从系统中获取参数值的估计方法,它是一种能够利用输入数据和输出数据预测系统输出的交易方案。基于NARX ANN模型测量数据的离线评价过程,对30年的层数变化进行了MSE为0,38641的评价。
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Identification of the Flip Folder Folding Machine Using Artificial Neuro Network Method with NARX (Nonlinear Auto Regressive Exogenous) Structure
Folding machine is a tool that is needed in the small and medium scale laundry industry that has a goal for the efficiency of production time. The flip folder is the main component of this tool, which functions to fold the clothes by moving to form a certain deflection angle where the movement process is controlled by the controller. The system modeling process is the first step to study the characteristics of the system. In a dynamic system, the form of linear modeling is approved difficult to obtain a model that represents the actual physical model. Selecting the structure of the NARX (Nonlinear Autoregressive eXogenous) model was chosen to obtain the dynamic nature of the system. An estimation method to obtain parameter values from the system used Artificial Neural Networks (ANN), which is a trading scheme to be able to predict the output of a system that uses input data and output. Based on the offline assessment process using measurement data obtained by the NARX ANN model on the variation of the number of layers in 30 with a value of MSE 0,38641.
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