Robust dynamic operation optimization in hot rolling production process

Author(s):  
Li Chen ◽  
Yang Yang ◽  
Lu Yang
2014 ◽  
Vol 53 (28) ◽  
pp. 11393-11410 ◽  
Author(s):  
Li Chen ◽  
Xianpeng Wang ◽  
Lixin Tang

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jun Zhang

Dynamic operation optimization has been utilized to realize optimal control problem for converter. The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. DE (differential evolution) with improved strategy is used to solve the proposed model for obtaining the set values of each operating variable, which is beneficial for further control. Simulation of actual production data shows the feasibility and efficiency of the proposed method. That proved that the proposed method solves the optimal control problem of converter steelmaking process as well.


2012 ◽  
Vol 157-158 ◽  
pp. 719-726
Author(s):  
Hai Xiong Wang ◽  
Ji Bin Li ◽  
Hai Jun Liu ◽  
Chang Sheng Wang

In order to carry out automatic transformation to the two-roll reversible hot-rolling mill of a aluminum plate production factory, firstly a series of mathematical models of aluminum plate hot-rolling parameters are established, then a new optimization algorithm which is suitable for aluminum plate rolling production combined with the various constraints in the rolling process is proposed, and rolling schedule optimization software system is developed. Finally, by measuring the process parameters in rolling production site and applying the optimized rolling schedule to the rolling production, many test data are obtained. The analysis of test results and evaluation of the practical production show that the mathematical models established have high accuracy compared with the old rolling schedule. The optimization schedule can not only ensure the production quality, but also has higher efficiency and less energy consumption.


2010 ◽  
Vol 36 (2) ◽  
pp. 282-288 ◽  
Author(s):  
Chun-Yue YU ◽  
Cheng-En WANG ◽  
Rong-Xia QU

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