基于改进型粒子群优化算法的双辊薄带振动铸轧压下控制系统优化

摘要/Abstract

摘要： 振动铸轧辊的周期性振动是诱发Kiss点波动的主要因素，亦可导致轧制力波动，最终造成铸轧薄带纵向厚度不均，为此，对粒子群优化算法进行改进，提出了在粒子群收缩因子算法基础上添加扰动因子的优化算法，并依托四种不同类型的测试函数对该算法进行了仿真分析。结合AMESim、MATLAB联合仿真平台进行仿真验证，并将该算法应用于双辊薄带振动铸轧机液压压下控制系统上进行实验验证，结果表明，在粒子群收缩因子算法基础上添加扰动因子的优化算法在收敛速度及求解精度上明显优于基本粒子群优化算法、粒子群收缩因子算法、带极值扰动的粒子群优化算法，使得实际辊缝宽度误差降低至0.1mm。该算法适用于双辊薄带振动铸轧的中试生产，增强了振动铸轧工艺的稳定性。

关键词: 双辊薄带振动铸轧, 粒子群优化算法, 液压压下控制系统, 联合仿真

Abstract: The periodic vibrations of the cast-rolling were the main factor that induced the fluctuation of Kiss points, which might also cause the rolling forces to fluctuate, eventually resulting in uneven thickness of the casted strips. To this end, the constriction factor PSO added extremum disturbed factor was created based on the PSO algorithm. Simulation based on four different type of test functions was made, which combined with AMESIM-MATLAB co-simulation model for verification. The algorithm was applied to the hydraulic screwdown control system of twin-roll thin strip vibration cast-rolling mill for experimental verification. The results show that the constriction factor PSO added extremum disturbed factor is superior to the basic PSO, constriction factor PSO and extremum disturbed PSO algorithms in convergence speed and solution precision, where the errors of the actual roll seam width are decreased to 0.1mm. It is suitable for the pilot production of twin-roll strip vibration cast-rolling, which enhances the stability of the processes.

Key words: twin-roll thin strip vibration cast-rolling, particle swarm optimization(PSO) algorithm, hydraulic screw-down control system, co-simulation

中图分类号:

TG333

孙明翰;许哲;郑立康;许志强;杜凤山. 基于改进型粒子群优化算法的双辊薄带振动铸轧压下控制系统优化[J]. 中国机械工程.

SUN Minghan;XU Zhe;ZHENG Likang;XU Zhiqiang;DU Fengshan. Optimization of Twin-roll Thin Strip Vibrating Casting Screw-down Control Systems Based on Improved PSO Algorithm[J]. China Mechanical Engineering.

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