摘要
为了尽量减少液压机压下系统控制过程的迭代次数并达到更高的求解精度,综合运用粒子群收缩因子算法与扰动因子构建得到PSO算法,再利用AMESim与Matlab联合仿真的方式对其实施验证。研究结果表明:通过对比PSO算法和其它各算法可以发现,此算法相对其它粒子群优化算法可以获得更快求解速度并提升了控制精度。并且由于此算法实现过程简单,为实现双辊薄带振动铸轧工业化应用提供了理论参考。设计了PSO-PID优化方法来控制轧制力发生明显周期性波动的情况,由此实现精确的压下控制,降低了轧制力的波动程度,实现精确控制辊缝宽度的效果。该研究对拓展轧机轧制过程中调控精度具有一定的意义,尤其是针对薄板的制造起到推进作用。
In order to minimize the number of iterations in the control process of the rolling mill hydraulic down system and achieve higher solving accuracy,the PSO algorithm was constructed by using particle swarm shrinkage factor algorithm and disturbance factor,and verified by AMESim and Matlab co-simulation.The research results show that the PSO algorithm and other algorithms can be found that compared with other particle swarm optimization algorithms,this algorithm can achieve faster solving speed and improve the control accuracy.And because of the simple implementation process of this algorithm,it provides a theoretical reference for the industrial application of twin-roll thin-strip vibration casting and rolling.The PSO-PID optimization method is designed to control the rolling force with obvious periodic fluctuation,thus to achieve accurate down control,reduce the rolling force fluctuation degree,and thus to achieve the effect of accurate control of roll gap width.The research has a certain significance for expanding the control precision in the rolling process,especially for the manufacturing of thin plate.
作者
苏力
薛峰
SU Li;XUE Feng(School of Electronic Engineering,Xi’an Aeronautical University,Xi’an 710077,China;School of Electronic Information,Northwestern Polytechnical University,Xi’an 710072,China)
出处
《自动化与仪表》
2022年第6期14-17,共4页
Automation & Instrumentation
基金
航空科学基金资助项目(2019ZH0T7001)。
关键词
轧机
压下系统
PSO-PID算法
控制精度
迭代次数
优化分析
rolling mill
press system
PSO-PID algorithm
control accuracy
iterations number
optimization analysis
