摘要
为提高热连轧带钢粗轧宽度控制精度,研究短行程控制数学模型和西门子RBF神经网络模型系统,并进行了离线仿真分析。离线模拟结果与西门子控制模型相吻合,具有很高的应用价值。
Mathematical model of short stroke control and SIEMENS RBF neural network model system were studied in order to improve the precision of hot strip roughing width control and the off - line simulation analysis was carried out. The off - line simulation results were in agreement with the SIEMENS control model with a high applica- tion value.
出处
《冶金设备》
2017年第B07期1-3,共3页
Metallurgical Equipment
关键词
热轧带钢
短行程控制
RBF神经网络
自学习
Hot rolling strip Short stroke control RBF neural network Self- learning
