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

Peligrad, A. A., Zhou, Erping ORCID: 0000-0002-0568-294X, Morton, D. and Li, L. (2002) System identification and predictive control of laser marking of ceramic materials using artificial neural networks. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 216 (2). pp. 181-190. ISSN 0959-6518

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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.

Item Type: Article
Additional Information: Full-text of this article is not available on this repository.
Uncontrolled Keywords: clay tiles,laser marking,neural network,control system,system identification,non-linear dynamic systems
Divisions: School of Engineering > Engineering
Depositing User: Scott Wilson
Date Deposited: 26 Nov 2013 12:52
Last Modified: 05 Mar 2018 10:20
Identification Number: 10.1243/0959651021541543
URI: http://ubir.bolton.ac.uk/id/eprint/465

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