Modeling and control of flatness in cold rolling mill using fuzzy petri nets Dosthosseini, R., Sheikholeslam, F., Askari, J. and Kouzani, A. Z. 2010, Modeling and control of flatness in cold rolling mill using fuzzy petri nets, in ICCA 2010 : Proceedings of the 8th IEEE International Conference on Control and Automation, IEEE, Piscataway, N.J., pp. 181-186, doi: 10.1109/ICCA.2010.5524063. Attached Files Name Description MIMEType Size Downloads kouzani-modelingandcontrol-2010.pdf Published version application/pdf 172.12KB 460 Title Modeling and control of flatness in cold rolling mill using fuzzy petri nets Author(s) Dosthosseini, R. Sheikholeslam, F. Askari, J. Kouzani, A. Z. orcid.org/0000-0002-6292-1214 Conference name IEEE International Conference on Control and Automation (8th : 2010 : Xiamen, China) Conference location Xiamen, China Conference dates 9-11 June 2010 Title of proceedings ICCA 2010 : Proceedings of the 8th IEEE International Conference on Control and Automation Editor(s) Chen, Ben M. Li, Maoquing Wang, Jianliang Luo, Jian Publication date 2010 Conference series International Conference on Control and Automation Start page 181 End page 186 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) Control Modelling Cold Rolling Mill Fuzzy Petri Nets Summary 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. ISBN 9781424451951 ISSN 1948-3449 Language eng DOI 10.1109/ICCA.2010.5524063 Field of Research 090602 Control Systems, Robotics and Automation 091302 Automation and Control Engineering Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category E1 Full written paper - refereed HERDC collection year 2010 Copyright notice ©2010, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30029966 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Engineering Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 10 Sep 2010, 13:05:19 EST Fri, 10 Sep 2010, 13:07:31 EST Fri, 10 Sep 2010, 13:08:10 EST Mon, 13 Sep 2010, 10:11:57 EST Wed, 15 Sep 2010, 12:27:12 EST Thu, 23 Sep 2010, 16:09:32 EST Fri, 24 Sep 2010, 10:27:23 EST Fri, 24 Sep 2010, 10:28:53 EST Fri, 24 Sep 2010, 10:29:24 EST Fri, 24 Sep 2010, 10:30:31 EST Fri, 24 Sep 2010, 10:31:27 EST Fri, 24 Sep 2010, 10:33:26 EST Fri, 24 Sep 2010, 10:34:51 EST Fri, 24 Sep 2010, 10:36:26 EST Tue, 23 Nov 2010, 09:03:32 EST Mon, 07 Feb 2011, 08:34:47 EST Mon, 07 Feb 2011, 08:35:53 EST Mon, 07 Feb 2011, 08:37:28 EST Fri, 16 Mar 2012, 18:16:31 EST Mon, 23 Sep 2013, 12:52:48 EST Tue, 06 Sep 2016, 15:52:37 EST Tue, 05 Dec 2017, 09:17:23 EST Fri, 07 Sep 2018, 15:03:58 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 1053 Abstract Views, 465 File Downloads  -  Detailed Statistics Created: Fri, 10 Sep 2010, 13:05:09 EST by Abbas Kouzani