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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 KouzaniToday, 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 - 186Publisher
IEEELocation
Xiamen, ChinaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2010-06-09End date
2010-06-11ISSN
1948-3449ISBN-13
9781424451951Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2010, IEEEEditor/Contributor(s)
B Chen, M Li, J Wang, J LuoTitle of proceedings
ICCA 2010 : Proceedings of the 8th IEEE International Conference on Control and AutomationUsage metrics
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