Decoupling control analysis of aluminum alloy pulse MIG welding process based on dynamic fuzzy neural networks

	Decoupling control analysis of aluminum alloy pulse MIG welding process based on dynamic fuzzy neural networks
	Huang, Jiankang1 ; Zhang, Gang2 ; Fan, Ding1 ; Shi, Yu2
	2013-09-01
发表期刊	Hanjie Xuebao/Transactions of the China Welding Institution
ISSN	0253360X
卷号	34 期号:9 页码:43-47
摘要	Considering the strong coupling of parameters, unstable and other key issues during aluminum alloy pulse MIG welding process, D-FNN structure and learning algorithm were introduced. The decoupling controllers were designed based on D-FNN. The dynamic decoupling control simulation of aluminum alloy pulse MIG welding multiple-input multiple-output (MIMO) process, setting the duty cycle of pulse current and wire feeding speed as inputs but wire extension and weld width as outputs, was investigated with synchronization, asynchronous and adding interference pulse. The simulation results indicate that D-FNN controller could real-time evolve rules, dynamically adjust the learning factors, completely decouple the MIMO process and meet the real-time control requirements of welding process. In addition, its fast response speed and good robustness provided a new real-time decoupling control method for stabilizing the aluminum alloy pulsed MIG welding process.
关键词	Aluminum alloys Controllers Fuzzy inference Fuzzy logic Fuzzy neural networks Gas metal arc welding Inert gas welding Learning algorithms MIMO systems Real time control Decoupling control methods Decoupling controllers Decoupling controls Dynamic decoupling control Interference pulse Multiple input multiple output process Pulse MIG welding System simulations
收录类别	EI
语种	中文
出版者	Harbin Research Institute of Welding
EI入藏号	20134616974432
EI主题词	Process control
EI分类号	538.2.1 Welding Processes - 541.2 Aluminum Alloys - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 723.4 Artificial Intelligence - 731 Automatic Control Principles and Applications - 732.1 Control Equipment
来源库	Compendex
分类代码	538.2.1 Welding Processes - 541.2 Aluminum Alloys - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 723.4 Artificial Intelligence - 731 Automatic Control Principles and Applications - 732.1 Control Equipment
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/112875
专题	材料科学与工程学院省部共建有色金属先进加工与再利用国家重点实验室
作者单位	1.State Key Laboratory of Gansu Advanced Non-Ferrous Metal Materials, Lanzhou University of Technology, Lanzhou 730050, China; 2.Key Laboratory of Non-Ferrous Metal Alloys, The Ministry of Education, Lanzhou University of Technology, Lanzhou 730050, China
第一作者单位	省部共建有色金属先进加工与再利用国家重点实验室
第一作者的第一单位	省部共建有色金属先进加工与再利用国家重点实验室
推荐引用方式 GB/T 7714	Huang, Jiankang,Zhang, Gang,Fan, Ding,et al. Decoupling control analysis of aluminum alloy pulse MIG welding process based on dynamic fuzzy neural networks[J]. Hanjie Xuebao/Transactions of the China Welding Institution,2013,34(9):43-47.
APA	Huang, Jiankang,Zhang, Gang,Fan, Ding,&Shi, Yu.(2013).Decoupling control analysis of aluminum alloy pulse MIG welding process based on dynamic fuzzy neural networks.Hanjie Xuebao/Transactions of the China Welding Institution,34(9),43-47.
MLA	Huang, Jiankang,et al."Decoupling control analysis of aluminum alloy pulse MIG welding process based on dynamic fuzzy neural networks".Hanjie Xuebao/Transactions of the China Welding Institution 34.9(2013):43-47.