ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

作     者：Gao Xiangdong Faculty of Mechanical and Electrical Engineering，Guangdong University of Technology， Guangzhou 510090，China Huang Shisheng South China University of Technology 

作者机构：Faculty of Mechanical and ELectrical Engineering Guangdong University of Technology Guangzhou 510090 South China University of Technology 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2002年第15卷第1期

页      面：53-56页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China and Provincial Natural Science Foundafion of Guangdong  China 

主　　题：Artificial neural network Fuzzy logic control Weld pool depth Seamtracking 

摘      要：An artificial neural network(ANN) and a self-adjusting fuzzy logiccontroller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are *** discussion is mainly focused on the modeling and control of the weld pool depth with ANN and theintelligent control for weld seam tracking with FLC. The proposed neural network can produce highlycomplex nonlinear multi-variable model of the GTAW process that offers the accurate prediction ofwelding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts thecontrol parameters on-line automatically according to the tracking errors so that the torch positioncan be controlled accurately.