基于MPC控制技术优化VPSA制氧工艺的模拟

邢瑞; 江南; 刘冰; 安亚雄; 汪亚燕; 张东辉

doi:10.11949/0438-1157.20190857

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基于MPC控制技术优化VPSA制氧工艺的模拟

分离工程 | 更新时间：2026-07-24

- 基于MPC控制技术优化VPSA制氧工艺的模拟
- Simulation of oxygen production via VPSA optimized based on MPC control strategy
- 化工学报 2020年71卷第2期页码：669-679
- 作者机构：
  
  化学工程联合国家重点实验室，天津大学化工学院化学工程研究所，天津 300072
- 作者简介：
  
  邢瑞（1995—），男，硕士研究生， 347929872@qq.com
  张东辉（1967—），男，博士，副研究员， donghuizhang@tju.edu.cn
- 基金信息：
  
  化学工程联合国家重点实验室开放课题(SKL-ChE-16B05)
- DOI：10.11949/0438-1157.20190857
  中图分类号： TQ 028.1
- 收稿：2019-07-25，
  
  修回：2019-12-24，
  
  网络首发：2020-08-14，
  
  纸质出版：2020-02-05
- 稿件说明：
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邢瑞, 江南, 刘冰, 安亚雄, 汪亚燕, 张东辉. 基于MPC控制技术优化VPSA制氧工艺的模拟[J]. 化工学报, 2020, 71(2): 669-679

XING Rui, JIANG Nan, LIU Bing, AN Yaxiong, WANG Yayan, ZHANG Donghui. Simulation of oxygen production , via VPSA optimized based on MPC control strategy[J]. CIESC Journal, 2020, 71(2): 669-679
邢瑞, 江南, 刘冰, 安亚雄, 汪亚燕, 张东辉. 基于MPC控制技术优化VPSA制氧工艺的模拟[J]. 化工学报, 2020, 71(2): 669-679 DOI： 10.11949/0438-1157.20190857.

XING Rui, JIANG Nan, LIU Bing, AN Yaxiong, WANG Yayan, ZHANG Donghui. Simulation of oxygen production , via VPSA optimized based on MPC control strategy[J]. CIESC Journal, 2020, 71(2): 669-679 DOI： 10.11949/0438-1157.20190857.

摘要

针对真空变压吸附制氧在gPROMS软件中建立了严格的数学模型，基于LiLSX吸附剂设计了两塔八步的真空变压吸附流程生产纯度为92%的O

。对此流程进行优化，其纯度和回收率有了明显的改进。在此基础上，引入实际生产中经常存在的如进料流量的变化以及吸附性能降低等扰动因素，使模拟工作更接近实际。根据产品气中O

纯度的反馈，采用模型辨识技术设计了MPC控制器，用于预测控制VPSA过程的动态行为。开环和闭环控制结果的对比显示，流程在设计的MPC控制下展现出更好的结果，这表明MPC控制策略可以明显改善空气分离制氧的生产过程。

Abstract

A rigorous mathematical model was established in the gPROMS software for vacuum PSA oxygen production. Based on the LiLSX adsorbent

a two-stage

eight-

step vacuum PSA process was designed to produce O

with a purity of 92%. Changes in feed flow rate as well as the decrease of the adsorption property were set as disturbances to make the simulation work more close to reality. Meanwhile

time duration was set to change consistently according to the feedback of O

purity in product. The system identification model was then adopted and was used to predict the dynamic behavior of the VPSA process and to develop an MPC controller. Detailed performance under open-loop and closed-loop was listed and compared. The results demonstrated that the model shows an enhanced performance with the presence of random disturbances under closed-loop control. This suggested that the MPC control strategy can be implied to improve the oxygen-production process.

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references

Helfferich F G . Principles of adsorption & adsorption processes, by D. M. Ruthven, John Wiley & Sons, 1984, xxiv + 433 pp [J ] . AIChE Journal , 1985 , 31 ( 3 ): 523 - 524 .

Ding Z Y , Han Z Y , Fu Q , et al . Optimization and analysis of the VPSA process for industrial-scale oxygen production [J ] . Adsorption , 2018 , 24 : 499 - 516 .

Zhu X Q , Liu Y S , Yang X , et al . Progress of adsorbent modified and process of pressure swing adsorption for oxygen production in China [J ] . Chem. Ind. Eng. Prog ., 2014 , 55 : 119 - 124 .

Li Y L , Liu Y S . Oxygen enrichment and its application to life support systems for workers in high-altitude areas [J ] . International Journal of Occupational and Environmental Health , 2014 , 20 ( 3 ): 207 - 214 .

Ruthven D M , Farooq S . Air separation by pressure swing adsorption [J ] . Gas Separation & Purification , 1990 , 4 ( 3 ): 141 - 148 .

刘应书 , 祝显强 , 杨雄 , 等 . 快速真空变压吸附制氧实验研究 [J ] . 医用气体工程 , 2016 , 1 : 29 - 32 .

Liu Y S , Zhu X Q ， Yang X , et al . An experimental study of rapid vacuum pressure swing adsorption for producing oxygen [J ] . Medical Gases Engineering , 2016 , 1 : 29 - 32 .

Mayne D Q , Rawlings J B , Rao C V , et al . Constrained model predictive control: stability and optimality [J ] . Automatica , 2000 , 36 ( 6 ): 789 - 814 .

Khajuria H , Pistikopoulos E N . Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems [J ] . Journal of Process Control , 2011 , 21 ( 1 ): 151 - 163 .

蒲荣 . 可编程控制器在变压吸附装置中的应用 [J ] . 天然气化工(C1化学与化工) , 1999 , 24 ( 1 ): 44 - 48 .

Pu R . Application of programmable controller in pressure swing adsorption device [J ] . Natural Gas Chemical Industry , 1999 , 24 ( 1 ): 44 - 48 .

Froisy J B . Model predictive control: past, present and future [J ] . Isa Transactions , 1999 , 33 ( 3 ): 235 - 243 .

Sircar S , Hanley B F . Production of oxygen enriched air by rapid pressure swing adsorption [J ] . Adsorption , 1995 , 1 ( 4 ): 313 - 320 .

Bitzer M . Model-based Nonlinear Tracking Control of Pressure Swing Adsorption Plants [M ] // Control and Observer Design for Nonlinear Finite and Infinite Dimensional Systems . Berlin : Springer , 2005 : 403 - 418 .

Kouramas K I , Faísca N P , Panos C , et al . Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming [J ] . Automatic , 2011 , 47 ( 8 ): 1638 - 1645 .

Khajuria H , Pistikopoulos E N . Optimization and control of pressure swing adsorption processes under uncertainty [J ] . AIChE Journal , 2013 , 59 ( 1 ): 120 - 131 .

Sereno C , Rodrigues A . Can steady-state momentum equations be used in modeling pressurization of adsorption beds [J ] . Gas Separation & Purification , 1993 , 7 ( 3 ): 167 - 174 .

Sun W N , Shen Y H , Zhang D H , et al . A systematic simulation and proposed optimization of the pressure swing adsorption process for N 2 /CH 4 separation under external disturbances [J ] . Industrial & Engineering Chemistry Research , 2015 , 54 ( 30 ): 7489 - 7501 .

丁兆阳 , 韩治洋 , 石文荣 , 等 . 快速变压吸附制氧动态传质系数模拟分析 [J ] . 化工学报 , 2018 , 69 ( 2 ): 759 - 768 .

Ding Z Y , Han Z Y , Shi W R , et al . Analysis of dynamic effective mass transfer coefficients of rapid pressure swing adsorption process for oxygen production [J ] . CIESC Journal , 2018 , 69 ( 2 ): 759 - 768 .

Chihara K , Yoneda I , Morishita S , et al . Simulation of pressure swing adsorption for air separation [J ] . Studies in Surface Science & Catalysis , 1986 , 28 : 563 - 570 .

Knaebel K S , Hill F B . Pressure swing adsorption: development of an equilibrium theory for gas separations [J ] . Chemical Engineering Science , 1985 , 40 ( 12 ): 2351 - 2360 .

Li D D , Zhou Y , Shen Y H , et al . Experiment and Simulation for Separating CO 2 /N 2 by dual-reflux pressure swing adsorption process [J ] . Chemical Engineering Journal , 2016 , 297 : 315 - 324 .

Banerje A , Arkun Y . Model predictive control of plant transitions using a new identification technique for interpolating nonlinear models [J ] . Process Control , 1998 , 8 ( 5 ): 441 - 457 .

Arefi M M , Montazeri A , Poshtan J , et al . Wiener-neural identification and predictive control of a more realistic plug-flow tubular reactor [J ] . Chemical Engineering Journal , 2008 , 138 ( 1 / 2 / 3 ): 274 - 282 .

Hasan M M F , Baliban R C , Elia J A , et al . Modeling, simulation, and optimization of postcombustion CO 2 capture for variable feed concentration and flow rate(2): Pressure swing adsorption and vacuum swing adsorption processes [J ] . Industrial & Engineering Chemistry Research , 2016 , 51 ( 48 ): 15665 - 15682 .

Joss L , Capra F , Gazzani M , et al . MO-MCS: an efficient multi-objective optimization algorithm for the optimization of temperature/pressure swing adsorption cycles [C ] // 26th European Symposium on Computer Aided Process Engineering . 2016 : 1467 - 1472 .

Yang H W , Yin C B , Jiang B , et al . Optimization and analysis of a VPSA process for N 2 /CH 4 separation [J ] . Separation & Purification Technology , 2014 , 134 ( 1 ): 232 - 240 .

Agarwal A , Biegler L T , Zitney S E . Simulation and optimization of pressure swing adsorption systems using reduced-order modeling [J ] . Industrial & Engineering Chemistry Research , 2009 , 48 ( 5 ): 2327 - 2343 .

Sentoni G B , Biegler L T , Guiver J B , et al . State-space nonlinear process modeling: identification and universality [J ] . AIChE Journal , 1998 , 44 ( 10 ): 2229 - 2239 .

Santos G C A . Dynamic study of the pressure swing adsorption process for biogas upgrading and its responses to feed disturbances [J ] . Industrial & Engineering Chemistry Research , 2013 , 52 ( 15 ): 5445 - 5454 .

Zhu Y . Multivariable system identification for process control [J ] . International Journal of Modelling Identification & Control , 2013 , 6 ( 1 ): 335 - 344 .

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