Neural networks in GTA weld modeling and control

Kumar Ramaswamy; George E. Cook; Kristinn Andersen; Gabor Karsai

doi:10.23919/acc.1989.4790167

Neural networks in GTA weld modeling and control

Kumar Ramaswamy^*, George E. Cook, Kristinn Andersen, Gabor Karsai

^*Corresponding author for this work

Faculty of Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

1 Citation (Scopus)

Abstract

A solution to modeling the gas tungsten arc welding process using a nonconventional technique is presented. This approach, a nonlinear modeling technique using neural networks, has exhibited the potential to learn to model the time responses of a nonlinear, multivariable system. The feasibility of this approach as an alternative to existing techniques is examined. Potential problems with this approach are discussed. A control architecture using a second neural network is suggested.

Original language	English
Pages	62-67
Number of pages	6
DOIs	https://doi.org/10.23919/acc.1989.4790167
Publication status	Published - 1989
Event	Proceedings of the 1989 American Control Conference - Pittsburgh, PA, USA Duration: 21 Jun 1989 → 23 Jun 1989

Conference

Conference	Proceedings of the 1989 American Control Conference
City	Pittsburgh, PA, USA
Period	21/06/89 → 23/06/89

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10.23919/acc.1989.4790167

Cite this

@conference{1c398772c2e84626b9a3de9f283adc6d,

title = "Neural networks in GTA weld modeling and control",

abstract = "A solution to modeling the gas tungsten arc welding process using a nonconventional technique is presented. This approach, a nonlinear modeling technique using neural networks, has exhibited the potential to learn to model the time responses of a nonlinear, multivariable system. The feasibility of this approach as an alternative to existing techniques is examined. Potential problems with this approach are discussed. A control architecture using a second neural network is suggested.",

author = "Kumar Ramaswamy and Cook, {George E.} and Kristinn Andersen and Gabor Karsai",

year = "1989",

doi = "10.23919/acc.1989.4790167",

language = "English",

pages = "62--67",

note = "Proceedings of the 1989 American Control Conference ; Conference date: 21-06-1989 Through 23-06-1989",

}

TY - CONF

T1 - Neural networks in GTA weld modeling and control

AU - Ramaswamy, Kumar

AU - Cook, George E.

AU - Andersen, Kristinn

AU - Karsai, Gabor

PY - 1989

Y1 - 1989

N2 - A solution to modeling the gas tungsten arc welding process using a nonconventional technique is presented. This approach, a nonlinear modeling technique using neural networks, has exhibited the potential to learn to model the time responses of a nonlinear, multivariable system. The feasibility of this approach as an alternative to existing techniques is examined. Potential problems with this approach are discussed. A control architecture using a second neural network is suggested.

AB - A solution to modeling the gas tungsten arc welding process using a nonconventional technique is presented. This approach, a nonlinear modeling technique using neural networks, has exhibited the potential to learn to model the time responses of a nonlinear, multivariable system. The feasibility of this approach as an alternative to existing techniques is examined. Potential problems with this approach are discussed. A control architecture using a second neural network is suggested.

UR - http://www.scopus.com/inward/record.url?scp=0024939833&partnerID=8YFLogxK

U2 - 10.23919/acc.1989.4790167

DO - 10.23919/acc.1989.4790167

M3 - Paper

AN - SCOPUS:0024939833

SP - 62

EP - 67

T2 - Proceedings of the 1989 American Control Conference

Y2 - 21 June 1989 through 23 June 1989

ER -

Neural networks in GTA weld modeling and control

Abstract

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