Computer simulation of neural network control system for CO2 welding process

被引:0
|
作者
Ding, Fan [1 ]
Yu, Shi [1 ]
Jianjun, Li [1 ]
Yuezhou, Ma [2 ]
Jianhong, Chen [2 ]
机构
[1] Lanzhou Univ Tech, Minist Educ, Key Lab Non Ferrous Metal Alloys, Lanzhou 730050, Peoples R China
[2] Lanzhou Univ Tech, State Key Lab Gansu New Non-ferrous Metal Mat, Lanzhou 730050, Peoples R China
来源
ROBOTIC WELDING, INTELLIGENCE AND AUTOMATION | 2007年 / 362卷
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, neural network control systems for decreasing the spatter of CO2 welding have been created. The Generalized Inverse Learning Architecture(GILA), the Specialized Inverse Learning Architecture(SILA)- I & II and the Error Back Propagating Model(EBPM) are adopted respectively to simulate the static and dynamic welding control processes. The results of simulation show that the SILA- I and EBPM have better properties. The factors affecting the simulating results and the dynamic response quality have also been analyzed.
引用
收藏
页码:117 / +
页数:3
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