Multivariable Intelligent Control for M.A.G. Welding Proces

  • Constantin Miholca “Dunarea de Jos” University of Galati
  • Viorel Nicolau “Dunarea de Jos” University of Galati
  • Cristian Munteanu “Dunarea de Jos” University of Galati
  • Dan Mihăilescu “Dunarea de Jos” University of Galati
Keywords: welding process, intelligent control, nonlinear model, neural network, reverse dynamic model

Abstract

A neural control technique, applied to the MAG (Metal-Active Gas) welding process, is presented in the paper. The static nonlinear model of welding process is based on experimental determinations. The geometric parameters of the welding beam are considered as output parameters of the MAG process (Bs, a, p), and they are measured for different step-variations of the input parameters (Ve, Vs, Ua). The analysis of the output dynamics was further used to model the MAG welding process using a 3-layer neural network with 6 hidden-layer neurons. In order to reject perturbations and cancel the stationary error, an error compensator was used, which consists of the reverse dynamic model connected to a proportional integrator controller. Simulation results for the multivariable neural controller are presented.

Published
2008-06-30
How to Cite
1.
Miholca C, Nicolau V, Munteanu C, Mihăilescu D. Multivariable Intelligent Control for M.A.G. Welding Proces. The Annals of “Dunarea de Jos“ University of Galati. Fascicle III, Electrotechnics, Electronics, Automatic Control, Informatics [Internet]. 30Jun.2008 [cited 4May2024];31(1):17-2. Available from: https://www.gup.ugal.ro/ugaljournals/index.php/eeaci/article/view/646
Issue
Vol 31 No 1 (2008)
Section
Articles

@ "Dunarea de Jos" University of Galati

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