APPLICATION OF NEURO-PREDICTIVE CONTROL TO LASER BEAM WELDING
A. Bollig*, H. Rake*, Ch. Kratzsch** and S. Kaierle**
* Institute of Automatic Control Aachen University of Technology, 52056 Aachen, Germany Phone: ++49-241-8027480, Fax: ++49-241-8022296 E-Mail: A.Bollig@irt.rwth-aachen.de
** Lehrstuhl für Lasertechnik Aachen University of Technology, 52056 Aachen, Germany
Welding with laser beams is an innovative technique, which leads to higher penetration depth and a narrower seam compared to conventional welding techniques. One significant criterion of the quality of a junction is the penetration depth. Within this article a predictive control scheme is presented that optimises the process input laser power by taking the future welding speed into account. For modelling this non-linear process an Artificial Neural Network (ANN) is applied. The GPC-algorithm with a linear model obtained by instantaneous linearization of the network is used. First results of the application on a real laser welding system are described.
Keywords: Neural networks, Predictive control, System identification, Linearization, On-line control
Session slot T-Th-M04: Neuro control systems/Area code 3e : Fuzzy and Neural Systems

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