Title
Geometry and Thermal Regulation of GMA Welding via Conventional and Neural Adaptive Control
Abstract
This paper investigates the application of conventional and neural adaptive control schemes to Gas Metal Arc (GMA) welding. The goal is to produce welds of high quality and strength. This can be achieved through proper on-line control of the geometrical and thermal characteristics of the process. The welding process is variant in time and strongly nonlinear, and is subject to many defects due to improper regulation of parameters like arc voltage and current, or travel speed of the torch. Adaptive control is thus naturally a very good candidate for the regulation of the geometrical and thermal characteristics of the welding process. Here four adaptive control techniques are reviewed and tested, namely: model reference adaptive control (MRAC), pseudogradient adaptive control (PAC), multivariable self-tuning adaptive control (STC), and neural adaptive control (NAC). Extensive numerical results are provided, together with a discussion of the relative merits and limitations of the above techniques.
Year
DOI
Venue
1997
10.1023/A:1007968630038
Journal of Intelligent and Robotic Systems
Keywords
Field
DocType
gas metal arc (GMA) welding,geometric characteristics,thermal characteristics,adaptive control,pseudogradient control,self-tuning control,neural adaptive control,regulation of GMA welding
Nonlinear system,Multivariable calculus,Control theory,Control engineering,Process control,Artificial intelligence,Arc welding,Adaptive control,Engineering,Artificial neural network,Welding,Robotics
Journal
Volume
Issue
ISSN
19
2
1573-0409
Citations 
PageRank 
References 
1
1.07
0
Authors
3
Name
Order
Citations
PageRank
s g tzafestas119423.21
G. G. Rigatos2798.92
E. J. Kyriannakis311.07