Speed control in AOI system by using neural networks algorithm

Chun-Jung Chen, L. Shiau, Tien-Chi Chen
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Abstract

This paper presents a two layer recurrent neural network employed in glass speed control transmitted by linear servo motor in Automated Optical Inspection (AOI) system platform. The recurrent neural network consists of an identifier and a controller, the identifier is used to catch a feedback signal from the position sensor and the controller is processed in microprocessor in order to supply an adaptive PWM signal. The glass in AOI is transmitted and controlled by linear servo motor. The PWM was processed by dsPIC30F30XX series microprocessor. The performance of the proposed method was demonstrated very good performance. The theoretic formulations of the proposed neural networks were derived. The stability of the proposed method was also analyzed and demonstrated.
基于神经网络算法的AOI系统速度控制
本文提出了一种双层递归神经网络用于自动光学检测系统平台中由直线伺服电机传输的玻璃速度控制。递归神经网络由标识符和控制器组成,标识符捕获位置传感器的反馈信号,控制器在微处理器处理后提供自适应PWM信号。AOI中的玻璃由直线伺服电机传送和控制。PWM由dsPIC30F30XX系列微处理器处理。实验结果表明,该方法具有良好的性能。推导了所提神经网络的理论表达式。对该方法的稳定性进行了分析和论证。
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