摘要
控制冷却是热轧钢材生产过程中控制与改善钢材质量的重要途径,带钢层流冷却温度控制是热轧带钢生产过程中控制冷却经常采用的一种主要技术方法;对层流冷却系统及层流冷却计算机控制系统进行了研究;根据人工神经网络具有处理非线性复杂过程的能力,对神经网络预测控制模型的工作原理进行了研究,并进行了仿真;仿真结果说明了冷却速率、终冷温度都得到了很好的控制,仿真结果接近目标结果。
Control cooling in hot rolling mill is a very important method to control and improve the quality of product. Laminar cooling control is one of control cooling, and coiling temperature is one important parameter of performance of hot strip. This dissertation studies the laminar cooling system and laminar cooling computer control system. Based on artificial neural network having the ability to handle non lin- ear complex process, the neural network model predictive control process have been studied, and simulation. Simulation results show that the cooling rate, the final cold temperatures have been well controlled the results of the simulation results closer to the target.
出处
《计算机测量与控制》
CSCD
北大核心
2012年第8期2111-2113,共3页
Computer Measurement &Control
基金
河南省科技发展计划(112102210332)
河南省教育厅自然科学研究计划(2010C520010)
关键词
热轧带钢
层流冷却
神经网络
卷取温度
hot strip
laminar cooling
neural network
coiling temperature
