A New Strategy of Integrated Control and On-line Optimization on High-purity Distillation Process  

作　　者：吕文祥 朱鹰 黄德先 江永亨 金以慧 

机构地区：[1]Department of Automation, Tsinghua University, Beijing 100084, China [2]Tsinghua National Laboratory for Information Science and Techology ,Beijing 100084, China

出　　处：《Chinese Journal of Chemical Engineering》2010年第1期66-79,共14页中国化学工程学报（英文版）

基　　金：Supported by the National High Technology Research and Development Program of China（2007AA04Z193）; the National Natural Science Foundation of China（60974008 60704032）

摘　　要：For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential（PID）control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.

关 键 词：distillation process control split ratio surrogate model optimization modified differential evolution 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] S858.28[自动化与计算机技术—控制科学与工程]