基于神经网络的输送机控制

2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T) Pub Date : 2020-10-06 DOI:10.1109/PICST51311.2020.9467934

O. Pihnastyi, G. Kozhevnikov

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引用次数: 2

摘要

本文主要研究了具有大量断面的输送机控制系统的主要流程参数的设计。在控制系统的设计中，采用了神经网络。验证了神经网络的结构，定义了输入层和输出层节点的形成规则。对模型的主要参数进行了辨识和分析。利用运输系统的分析模型，形成训练神经网络的数据集。制定了运输系统质量的标准。对于给定的输运系统质量判据，定义了Pontryagin函数并给出了伴随方程组。它允许计算运输系统的最优控制。在计算中采用了附加的运输系统模型，输出节点为控制节点。给出了研究结果的图形表示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Control of a Conveyor Based on a Neural Network

The present study is devoted to the design of main flow parameters a conveyor control system with a large number of sections. For the design of the control system, a neural network is used. The architecture of the neural network is justified and the rules for the formation of nodes for the input and output layers are defined. The main parameters of the model are identified and analyzed. The data set for training the neural network is formed using the analytical model of the transport system. The criterion for the quality of the transport system is written. For the given criterion for the quality of the transport system, the Pontryagin function is defined and the adjoint system of equations is given. It allows calculating optimal control of the transport system. For calculation is used additional model of the transport system with output nodes which are controls. A graphical representation of the results of the study is given.

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来源期刊

2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T)

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