Integrated Intelligence Control Based on Fuzzy and AI for Reheating Furnace
Yingxin Liao*, **, Min Wu*, Kaoru Hirota***, Fangyan Dong***, and Weihua Cao*
*School of Information Science and Engineering, Central South University, Changsha, 410083, China
**School of Electron and Information Engineering, Central South Forestry University, Changsha, 410004, China
***Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
An integrated intelligence control method based on fuzzy and artificial intelligence (AI) is proposed aiming at combustion control of reheating furnace in steel rolling mill. Both fuzzy and AI strategies are used to solve problems of the bigger overshoot and the slower response in conventional hearth temperature control when gas pressure and heat value are frequently and acutely varied. The fuel-air ratio optimization and flux tracking modules based on AI respectively decrease fuel consumption and prolong the lifetime of actuators. The proposed method is implemented on an intelligence controller and distributed controllers, and the field test on two reheating furnaces in Lianyuan Iron and Steel Group Co. Ltd., Loudi, Hunan, China confirms that hearth temperature standard deviation, fuel consumption, and high temperature oxidation of billet are respectively decreased by 50%, 12%, and 10% over the current manual method. The proposed method delivers superior performance for reheating furnace in steel industry, but also it can be applied for other type furnaces in steel industry and in other industries, where further performance improvement might be achieved by adding a self-organizing capability to the fuzzy logic and AI control.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.