Abstract
Laser marking of ceramic materials is a multivariable non-linear process. Real-time control of the process requires the understanding of system dynamics and parameter interaction. In this work, direct inverse control (DIC) and non-linear predictive control (NPC) based on artificial neural networks were applied. The output variable considered for the laser clay tile-marking process was melt pool temperature. The input quantities investigated were laser power and traverse speed. The results show that the NPC accomplished a better reference tracking than the DIC. It was also found that the beam velocity and laser power could well be used to counteract disturbances.
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Schedule a callMore From: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
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