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板形控制中引入功效函数有助于更充分地发挥轧机的板形控制能力,改善带钢的板形质量.建立了基于功效函数的冷轧机板形控制模型,同时给出了相应的自学习模型,并将其应用到1450冷连轧机组的生产实践,所建立的功效系数模型及其自学习技术不但计算精度较高,能够满足工程需要而且计算过程非常稳定,计算速度能够得到保证,达到现场实际要求,取得了良好的使用效果,具有进一步推广应用的价值.

The concept of evaluation function is defined to describe the characteristics of shape contr01.The corresponding shape control model based on the evaluation function was given out and self-learning model was established and used on 1450 tandem mill.The model of evaluation coefficient and its self-learning are calculated accurately which can meet the engineering needs,the calculation process is very stable and the calculation speed can be assured.The model meets the actual needs of the field and gets good results,so the model can be popularized further.

参考文献

[1] Claire Nappezetal.Control of Strip Flatness in Cold Rolling[J].Iron & Steel Engineers,1997(04):42.
[2] 张清东,黄纶伟,周晓敏.宽带钢轧机板形控制技术比较研究[J].北京科技大学学报,2000(02):177.
[3] 杨荃;陈先霖;徐耀寰 等.应用变接触长度支承辊提高板形综合调控能力[J].钢铁,1995,30(02):48.
[4] 杨景;王洪瑞;方一鸣.1850mm铝带冷轧机板形控制软件简介[J].冶金自动化,1995(01):18.
[5] 贾春玉,王建国,李兴东,王英华.人工智能技术在板形控制中的应用[J].冶金设备,2003(04):8-13.
[6] 王国栋;刘相华.金属轧制过程人工智能优化[M].北京:冶金工业出版社,2000
[7] Minsuk Shim;Kwang Y Lee.Intelligent Controller Design for the Flatness Control in a Cold Rolling Process[A].Orlando:IEEE,2001:2720.
[8] 刘芳,刘民,吴澄.基于模块化模糊子系统的分层模糊神经网络[J].控制与决策,2006(03):281-284.
[9] 陈丽,李建更,乔俊飞,王笑波.UC轧机二次型板形缺陷模糊神经网络控制[J].控制工程,2005(05):438-441.
[10] Wong Ching-Chang;Chen Chia-Chong.A Hybrid Clustering and Gradient Descent Approach for Fuzzy Modeling[A].New York:IEEE Press,1999:686.
[11] 王军生;白金来;刘相华.带钢冷连轧原理与过程控制[M].北京:科学出版社,2009
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