System identification and predictive control of laser marking of ceramic materials using artificial neural networks

A. A. Peligrad, E. Zhou, D. Morton, L. Li

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)181-190
Number of pages9
JournalProceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
Volume216
Issue number2
DOIs
Publication statusPublished - 2002

Keywords

  • Clay tiles
  • Control system
  • Laser marking
  • Neural network
  • Non-linear dynamic systems
  • System identification

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