Application of advanced process control in xylene distillation unit
|更新时间:2025-12-10
|
Application of advanced process control in xylene distillation unit
CIESC JournalIssue 1, Pages: 193-198(2009)
作者机构:
1. 清华大学自动化系
2. 清华信息科学与技术国家实验室
作者简介:
基金信息:
DOI:
CLC:
Online First:05 January 2009,
Published:05 January 2009
稿件说明:
移动端阅览
Lü Wenxiang, SHI Dapeng, HUANG Dexian, et al. Application of advanced process control in xylene distillation unit[J]. CIESC Journal, 2009, (1): 193-198.
DOI:
Lü Wenxiang, SHI Dapeng, HUANG Dexian, et al. Application of advanced process control in xylene distillation unit[J]. CIESC Journal, 2009, (1): 193-198.DOI:
Application of advanced process control in xylene distillation unit
Advanced process control(APC)technology has been increasingly applied in petro-chemical plants to ensure product quality,increase production yield and save energy.Xylene distillation unit,as one of the most important units in aromatics production,has difficulties in control and has tremendous energy consumption in the reboiler furnace.Especially there is large noise and even steady error sometimes in the measurement of the outlet vaporization fraction of the reboiler furnace,for which the general PID control for the vaporization fraction cannot work.In order to solve the problems in xylene distillation unit,the state space models of xylene column and its reboiler furnace were made by analyzing its mechanism and using practical data.Based on the state feedback predictive control,the advanced process control system was developed and applied in the distillation unit.Using a model from the fuel to the bottom temperature of the column directly without state feedback of practical vaporization fraction,the measurements of vaporization fraction with large noise were ignored from the temperature control strategy.So the operating stability and the separating performance can be improved,and then the energy consumed can be reduced by the optimization of reflux and furnace load.And also,the optimization of the fuel,which means the increase of fuel gas and the decrease of fuel oil,can get more economical benefit.Two application cases show the advantages of the control system.
Recent advances in machine learning for modeling and control of crystallization processes
Construction of transition metal-based nitrogen-doped carbon and their desulfurization performance
Controlled synthesis of Bi2MoO6/MoO3 composite fibers via in-situ hydrothermal method and their high-efficiency photocatalytic hydrogen production performance
Prediction of biomass pyrolysis product yield based on machine learning algorithms
Heat transfer mechanisms, bottleneck identification and optimization in heat exchanger networks under variable operating conditions