Integrated Optimization of Production Scheduling and Explicit Model Predictive Control for Batch Process Based on SEN Framework

doi:10.12422/j.issn.1672-6952.2025.04.010

Journal of Liaoning Petrochemical University ›› 2025, Vol. 45 ›› Issue (4): 80-88.DOI: 10.12422/j.issn.1672-6952.2025.04.010

• Information and Control Engineering • Previous Articles Next Articles

Integrated Optimization of Production Scheduling and Explicit Model Predictive Control for Batch Process Based on SEN Framework

Yue WANG¹(), Xiaohui GUO², Yuting JIN¹, Xin JIN¹()

^1.School of Information and Control Engineering，Liaoning Petrochemical University，Fushun Liaoning 113001，China
^2.Weichai Lovol Smart Agriculture Technology Company Limited，Weifang Shandong 261200，China

Received:2024-02-22 Revised:2024-07-14 Published:2025-08-25 Online:2025-07-24
Contact: Xin JIN

基于SEN框架的间歇过程生产调度与显式模型预测控制集成优化

王越¹(), 郭小晖², 金雨婷¹, 金鑫¹()

^1.辽宁石油化工大学信息与控制工程学院，辽宁抚顺 113001
^2.潍柴雷沃智慧农业科技股份有限公司，山东潍坊 261200

通讯作者: 金鑫
作者简介:王越（1985⁃），女，博士，副教授，从事生产计划和调度的建模及优化、调度与控制协同优化方面的研究；E⁃mail：wangyue@lnpu.edu.cn。
基金资助:
辽宁省教育厅基本科研面上项目(LJKZ0400)

Abstract

Abstract:

Synchronous method is used to establish an integrated model for batch process production scheduling and control. In the scheduling section, a production scheduling model is established based on the State Equipment Network (SEN) and the unit?specific event?based continuous time modeling method; the integrated model of scheduling and control belongs to a mixed integer dynamic optimization problem, and solving it requires a large amount of complex computation, in order to alleviate the burden of online computing, Explicit Model Predictive Control (EMPC) is utilized for offline solving; the MPT toolbox is used to solve the dynamic problem of EMPC; introducing binary variables, converting the obtained explicit control solution into explicit linear constraints, and adding them to the common constraint objective in the scheduling model; through case analysis, the optimization results were compared and analyzed with the pure scheduling model, and the economic feasibility of the integrated model is verified.

Key words: Scheduling of batch process, State equipment network, Integrated model, Explicit model predictive control

摘要：

采用同步法建立间歇过程生产调度和控制的集成框架模型。在调度部分，基于状态设备网络（SEN）和特定单元事件点连续建模法建立生产调度模型；调度和控制的集成模型属于混合整数动态优化问题，求解复杂且计算量大，为了解决在线计算负担重的问题，采用显式模型预测控制（EMPC）进行离线求解；使用MPT工具箱解决EMPC动态问题；引入二进制变量，将求解得到的显式控制解转换为显式线性约束，并将其添加到调度模型中共同约束目标；通过算例分析，对优化结果与纯调度模型进行了对比分析，验证了集成模型的经济性。

关键词: 间歇过程生产调度, 状态设备网络, 集成模型, 显式模型预测控制

CLC Number:

TH166

Yue WANG, Xiaohui GUO, Yuting JIN, Xin JIN. Integrated Optimization of Production Scheduling and Explicit Model Predictive Control for Batch Process Based on SEN Framework[J]. Journal of Liaoning Petrochemical University, 2025, 45(4): 80-88.

王越, 郭小晖, 金雨婷, 金鑫. 基于SEN框架的间歇过程生产调度与显式模型预测控制集成优化[J]. 辽宁石油化工大学学报, 2025, 45(4): 80-88.

Figures/Tables 11

Fig.1 Integrated framework for scheduling and control

Fig.2 Connection between scheduling and control level

Fig.3 State equipment network diagram

Table 1 Reactor adaptation

设备	操作状态	容积/L
加热器	加热	100
反应器1	反应1、2、3	50
反应器2	反应1、2、3	80
分离器	分离	200

Table 2 Market information data

物料状态	价格/美元	初始量	容量/L
原料A	12.00	无限	无限
原料B	12.00	无限	无限
原料C	12.00	无限	无限
热物料A	0	0	100
AB混合物料	0	0	200
BC混合物料	0	0	150
混合物E	0	0	200
产品1	23.05	0	无限
产品2	30.30	0	无限

Fig.4 Batch stirring kettle system

Fig.5 [0，0.35] Partition of control solution and explicit control solution

Fig.6 [0.35，0.78] Partition of control solution and explicit control solution

Fig.7 [0.78，1.00] Partition of control solution and explicit control solution

Fig.8 Gantt chart of the ensemble method

Fig.9 Gantt chart of pure scheduling method

References 24

[1]	沈鹏.零等待间歇生产过程智能算法研究［D］.无锡：江南大学，2021.
[2]	于蕾.基于多向典型变量分析的间歇过程监控方法研究［D］.青岛：中国石油大学（华东），2020.
[3]	BA L，LI Y，YANG M S，et al.A mathematical model for multiworkshop IPPS problem in batch production［J］.Mathematical Problems in Engineering，2018，2018（1）：7948693.
[4]	刘伟，苏成利.基于MPCA⁃MHMT的多阶段间歇过程监控研究［J］.辽宁石油化工大学学报，2013，33（2）：56⁃59.
	LIU W，SU C L.Multi⁃way batch process monitoring based on MPCA⁃MHMT［J］.Journal of Liaoning Shihua University，2013，33（2）：56⁃59.
[5]	徐源，刘蔷，刘武，等.基于重要用户优先服务策略的天然气管网优化调度方法研究［J］.辽宁石油化工大学学报，2014，34（6）：35⁃41.
	XU Y，LIU Q，LIU W，et al.The study of natural gas pipeline network optimization scheduling method based on service priority of important user［J］.Journal of Liaoning Shihua University，2014，34（6）：35⁃41.
[6]	WANG Y，JIN X，LU S.Enhanced discrete time formulation for a short⁃term batch process scheduling problem with utility constraints［J］.Industrial & Engineering Chemistry Research，2019，58（31）：14559⁃14568.
[7]	LI D，RAKOVITIS N，ZHENG T C，et al.Novel multiple time⁃grid continuous⁃time mathematical formulation for short⁃term scheduling of multipurpose batch plants［J］.Industrial & Engineering Chemistry Research，2022，61（43）：16093⁃16111.
[8]	Ierapetritou M G，Floudas C A.An Improved RTN continuous⁃time formulation for the short⁃term scheduling of multipurpose batch plants［J］.Industrial & Engineering Chemistry Research，2001，40（9）：2059⁃2068.
[9]	CASTRO P M，GROSSMANN I E，ZHANG Q.Expanding scope and computational challenges in process scheduling［J］.Computers & Chemical Engineering，2018，114：14⁃42.
[10]	CASTRO P M.Optimal scheduling of a multiproduct batch chemical plant with preemptive changeover tasks［J］.Computers & Chemical Engineering，2022，162：107818.
[11]	YEOMANS H，GROSSMANN I E.A systematic modeling framework of superstructure optimization in process synthesis［J］.Computers & Chemical Engineering，1999，23（6）：709⁃731.
[12]	闫雪丽，韩豫鑫，顾幸生.基于状态设备网络的改进间歇生产调度模型［J］.化工学报，2018，69（3）：913⁃922.
	YAN X L，HAN Y X，GU X S.Improved schedule model for batch production by state unit network［J］.CIESC Journal，2018，69（3）：913⁃922.
[13]	NIE Y S，BIEGLER L T，WASSICK J M.Integrated scheduling and dynamic optimization of batch processes using state equipment networks［J］.AIChE Journal，2012，58（11）：3416⁃3432.
[14]	JI N，GU X S.Integration of scheduling and control for batch process based on generalized benders decomposition approach with genetic algorithm［J］.Computers & Chemical Engineering，2021，145：107166.
[15]	ANDRÉS⁃MARTÍNEZ O，RICARDEZ⁃SANDOVAL L A.A switched system formulation for optimal integration of scheduling and control in multi⁃product continuous processes［J］.Journal of Process Control，2021，106：94⁃109.
[16]	DIAS L S，IERAPETRITOU M G.Integration of scheduling and control under uncertainties：Review and challenges［J］.Chemical Engineering Research and Design，2016，116：98⁃113.
[17]	雷建，王润孝，段清娟，等.流程工业生产调度与控制集成系统研究［J］.计算机应用，2006，26（5）：1193⁃1195.
	LEI J，WANG R X，DUAN Q J，et al.Study of integrated scheduling and control system for process industry［J］.Computer Applications，2006，26（5）：1193⁃1195.
[18]	CHU Y F，YOU F Q.Integration of production scheduling and dynamic optimization for multi⁃product CSTRs：Generalized benders decomposition coupled with global mixed⁃integer fractional programming［J］.Computers & Chemical Engineering，2013，58：315⁃333.
[19]	修晓杰.显式模型预测控制中点定位算法研究［D］.杭州：浙江工业大学，2019.
[20]	KATZ J，PAPPAS I，AVRAAMIDOU S，et al.Integrating deep learning models and multiparametric programming［J］.Computers & Chemical Engineering，2020，136：106801.
[21]	SCHIRRER A，MAYRHOFER J，JAKUBEK S.Accurate piecewise⁃affine time⁃discrete modeling of hysteresis⁃coupled system dynamics［J］.IFAC⁃PapersOnLine，2018，51（15）：156⁃161.
[22]	LI H，WANG S Q，SHI H Y，et al.Two⁃dimensional iterative learning robust asynchronous switching predictive control for multiphase batch processes with time⁃varying delays［J］.IEEE Transactions on Systems，Man，and Cybernetics：Systems，2023，53（10）：6488⁃6502.
[23]	郭海峰.Internet下双渠道闭环供应链动态模型及其预测控制［J］.计算机集成制造系统，2018，24（12）：3157⁃3164.
	GUO H F.Dynamic model and model predictive control of dual⁃channel closed⁃loop supply chain on internet［J］.Computer Integrated Manufacturing Systems，2018，24（12）：3157⁃3164.
[24]	杨璞.基于PWA模型的显式模型预测控制与形式验证［D］.青岛：中国石油大学（华东），2016.

Integrated Optimization of Production Scheduling and Explicit Model Predictive Control for Batch Process Based on SEN Framework

基于SEN框架的间歇过程生产调度与显式模型预测控制集成优化

HTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 11

References 24

Related Articles 1

Recommended Articles

Metrics