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Modeling and control of flatness in cold rolling mill using fuzzy petri nets

conference contribution
posted on 2010-01-01, 00:00 authored by R Dosthosseini, F Sheikholeslam, J Askari, Abbas KouzaniAbbas Kouzani
Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.

History

Event

IEEE International Conference on Control and Automation (8th : 2010 : Xiamen, China)

Pagination

181 - 186

Publisher

IEEE

Location

Xiamen, China

Place of publication

Piscataway, N.J.

Start date

2010-06-09

End date

2010-06-11

ISSN

1948-3449

ISBN-13

9781424451951

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2010, IEEE

Editor/Contributor(s)

B Chen, M Li, J Wang, J Luo

Title of proceedings

ICCA 2010 : Proceedings of the 8th IEEE International Conference on Control and Automation

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