摘要
采用线性回归、神经网络、自校正模糊控制等技术结合热能专家知识与现代控制理论,建立前馈-反馈-修正-指导模型。根据焦化厂的生产需求,建立了专有控制平台和数据采集设备,进行模型计算和数据检测,并与原有集散控制系统进行集成和通信,完成系统的智能优化。
Combining linear regression,neural net and self tuning fuzzy control technology with expert knowledge of heat energy and modern control theory,the model of Feed forward-Feed back-Revise-Guide is established. Based on the production requirement of coking plant,special control platform and data collection devices are provided for model calculation and data detection. Integrated and communicated with the existing DCS control system,the heating control system is intelligently optimized.
出处
《燃料与化工》
2016年第1期17-20,共4页
Fuel & Chemical Processes
关键词
焦炉加热
智能优化
直行温度
火落时间
Coke oven heating
Intelligent optimization
Longitudinal temperature
Net coking time
