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• W1973729728 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." @default.
• W1973729728 created "2016-06-24" @default.
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• W1973729728 date "2002-03-01" @default.
• W1973729728 modified "2023-09-22" @default.
• W1973729728 title "System identification and predictive control of laser marking of ceramic materials using artificial neural networks" @default.
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• W1973729728 doi "https://doi.org/10.1243/0959651021541543" @default.
• W1973729728 hasPublicationYear "2002" @default.
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