连铸二次冷却智能优化控制的研究

Research on Intelligent Control of Secondary Cooling of Continuous Casting

针对连铸二冷目标温度控制法存在的系统不稳定、水量计算波动大等问题,以连铸二冷温度场数值计算为基础,采用在冶金约束条件允许下的变化目标温度,变化初始水量的方法,解决二冷动态控制实施过程中存在的问题。运用神经网络对函数的逼近能力与自学习能力构造目标温度控制模型(TTANN)、二冷水控制模型(IWANN)、设计智能PID控制器,与连铸坯温度计算模型组成连铸二冷控制系统,实现连铸二冷动态优化控制。仿真结果表明,温度动态控制精度小于12℃。

Based on numerical calculation of strand temperature field, using variable aim temperature with metallurgical restrictions and variable initial water flow rate, the unsteadiness and large difference between calculated and actual water flow rate of secondary cooling control can be solved. Using the ability of approaching function and selflearning of neural networks, the models of target temperature control （TTANN） and initial water flow rate control （IWANN） were set up. AI PID controller was designed. Then the dynamic control system of secondary cooling in continuous casting was developed. The system is composed of two models, controller and temperature calculation model. The results of simulation test show that the error of bloom surface temperature is less than 12℃.