Title :
Adaptive Interval Model Control of Arc Welding Process
Author :
Zhang, John ; Walcott, Bruce L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Kentucky Univ.
Abstract :
The welding process is typically uncertain and its dynamics may vary with welding conditions. To control this process, robust algorithms such as the interval model control proposed by Zhang and Kovacevic (1997) are needed. To improve the response speed and system performance, the authors developed an adaptive interval model control system for keyhole plasma arc welding process in this study. The developed system identifies the process parameters online, converts the identification results to the intervals in Zhang and Kovacevic´s algorithm (Zhang and Kovacevic 1997), and uses a prefilter to eliminate the effect of the keyhole process´ fluctuation on the control system. Experiments comparing the adaptive interval model control system with its nonadaptive counterpart have been conducted to verify the effectiveness of the former in achieving fast response speed when the manufacturing conditions or the set-point vary
Keywords :
adaptive control; arc welding; control nonlinearities; control system analysis; parameter estimation; process control; time-varying systems; uncertain systems; adaptive interval model control; dynamical systems; fluctuation elimination; keyhole plasma arc welding process; online process parameter identification; uncertain systems; Adaptive control; Control system synthesis; Control systems; Fluctuations; Plasma welding; Process control; Programmable control; Robust control; System performance; Virtual manufacturing; Adaptive control; manufacturing; robustness; uncertain systems; welding;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2006.880215