摘要
针对热轧带钢卷取温度控制的不确定性和时变性, 利用系统优化与模型参数的自适应控制热输出辊道上带钢温度. 从控制模式、冷却策略、段跟踪和模型的再计算以及学习系数的读取等方面对系统进行了优化. 根据实际工艺状况, 实时采集现场数据对层冷模型中的参数进行自适应调整, 并就组别分类、空冷/水冷系数的回归分析进行了研究. 实践结果表明： 采用这种方法能满足现场需要, 卷取温度控制精度较高, 基本在-15～15 ℃范围内;控制效果和带钢性能良好.
Due to the uncertainty and its variation with time of the coiling temperature control, system optimization and the self-adaptation of model parameters were adopted to control strip temperature on run-out table. The optimization of laminar cooling system was completed, including control mode, cooling strategy, segment track, re-calculating of model and learn-coefficients reading. According to practical status, the self-adaptation of model parameter was proposed based on the on-line measured data. Group classification and coefficients regression of air/water cooling were studied. The application results show that the method can meet the locale need. High precise control of coiling temperature features the cooling system, and the deviation of coiling temperature is within -- 15 - 15℃. Satisfactory control and significant properties are obtained.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第2期317-323,共7页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(50104004)
关键词
热轧带钢
层流冷却
优化
参数自适应
回归
hot rolling strip
laminar cooling
optimization
parameter self-adaptation
regression
