The 3D weld pool surface in gas tungsten arc welding (GTAW) is characterized by its width, length, convexity and measured in real-time using an innovative machine vision system. The dynamic response of these characteristic parameters to welding current and speed as control variables is modeled. Based on the identified dynamic model, a predictive control algorithm is developed to control these characteristic parameters. The proposed algorithm is given in a closed form and no online optimization is required. Welding experiments confirm that the developed control system is effective in achieving the desired 3D weld pool surface geometry despite various disturbances.
|Number of pages||12|
|Journal||Control Engineering Practice|
|State||Published - Nov 2013|
Bibliographical noteFunding Information:
This work is funded by the National Science Foundation under Grant CMMI-0927707 and IIS-1208420 . Y.K. Liu would like to thank W.J. Zhang at the Welding Research Laboratory, University of Kentucky, for his help in conducting welding experiments.
- Machine vision
- Predictive control
- Weld pool geometry
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics