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.
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.
Field of Research
090602 Control Systems, Robotics and Automation 091302 Automation and Control Engineering
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 email@example.com.
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 firstname.lastname@example.org.