Multi-Objective Optimization for Rolling Schedule of High Strength Sheet Based on ACPSO

Abstract:

Rolling schedule is an important parameter in high strength production of cold tandem rolling process, and the reasonable rolling schedule setting is important to cutting down energy consumption of unit, endurance of product stable and improving flatness as well as surface quality of sheet. Consequently, according to lots of theory research and spot experiment, taking relative balance of rolling force, flatness well of finished sheet and minimal rolling power as the control goal, the multi-object model for high strength sheet is built. Simultaneously, considering that PSO algorithm has shortcomings of initial randomness and premature convergence, the ACPSO algorithm is proposed which takes advantage of periodicity of the chaos motion and the inertial weight is adjust according to premature convergence extent of particle swarm and accommodate value of individual. It can improve convergence speed and accuracy. When the improved PSO algorithm is applied into rolling schedule model, it has good effect in spot experiment and productive practice.

• Periodical: Advanced Materials Research (Volumes 887-888)
• Pages: 1333-1340
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.887-888.1333
• Online since: February 2014
• Authors: Wei Tang*, Xin Yi Ren, Hui Min Gao, Shao Fei Wang
• Keywords: ACPSO Algorithm, Cold Tandem Rolling, High Strength Sheet, Multi-Objective Optimization (MOP), Rolling Schedule

References

[1] Li Yang, Liu Han-wu, Du Yun-hui. Application status and development direction of advanced high strength sheet used by motor car [J]. Materials Review, 2011, 25(7): 101.

[2] Cao Hong-de. Plastically deform mechanics basis and rolling theory [M]. Beijing: Metallurgy Industry Press, (1981).

[3] Wu Bin, Zhang Qing-dong, Zhang Xiao-feng. Effect of roll shape configuration of cold continuous mill on high-strength strip profil [J]. Steel Rolling, 2012, 29(1): 19.

[4] Peng Peng. Coupling relation and decoupling control research of wide strip cold tandem rolling mill [D]. Beijing: Beijing Technology University, 2008: 41.

[5] Wang Ling. Application of Two Intelligent Optimum Algorithms [M]. Beijing: Tsinghua University Press, (2001).

[6] Yang Hui-xian, Liu Zi-wen, Wang Jun. Modified PSO Hybrid Algorithm [J]. Journal of Computer Applications, 2010, 30(6): 1516.

[7] Chen Ru-qing, Yu Jin-shou. Study and Application of Chaos-Particle Swarm Optimization-based Hybrid Optimization Algorithm [J]. Journal of System Simulation, 2008, 20(6): 685.

[8] Gao Shang, Yang Jing-yu. Research on Chaos Particle Swarm Optimization Algorithm [J]. Pattern Recognition and Artificial Intelligence, 2006, 19(2): 266.

[9] Liu Wei, Liu Peng; Dou Qian. Application of PSO for Parameter Identification of Exciting System Based on Measured Data [J]. Guangxi Electric Power, 2009, 1: 37.