Chao Ren, Peng Tian, Guochao Meng, Dongliang Chen, Assoc. Prof. Zhonglin Zhang, Prof. Xiaogang Hao
The Rectisol process plays a pivotal role in syngas purification for clean coal utilization. Feedstock variations during gasification induce syngas flow and composition fluctuations, necessitating adaptive process control. This study develops both proportional–integral–derivative (PID) and model predictive control (MPC) strategies for the CO2 absorption column. The MPC controller was developed in MATLAB Simulink and innovatively integrated with Aspen Plus Dynamics through the AMSimulation interface module for co-simulation. The control strategies were evaluated under ±10 % flow and ±2 % CO2 concentration disturbances, with purified gas quality assessed through response time (RT), overshoot (OS), and the integral of absolute error multiplied by time (ITAE). The data-driven MPC strategy exhibits enhanced robustness against flow and composition variations compared to conventional PID control. The study offers actionable guidance for control system design in process industries.
低温甲醇工艺在合成气净化中起着关键作用。气化过程中的原料变化引起合成气流量和成分波动,需要自适应过程控制。本研究为二氧化碳吸收塔开发了比例-积分-导数(PID)和模型预测控制(MPC)策略。MPC控制器是在MATLAB Simulink中开发的,并通过AMSimulation接口模块与Aspen Plus Dynamics创新地集成在一起,进行联合仿真。在±10%的流量和±2%的CO2浓度干扰下,对控制策略进行了评估,并通过响应时间(RT)、超调量(OS)和绝对误差乘以时间的积分(ITAE)来评估净化后的气体质量。与传统的PID控制相比,数据驱动的MPC策略对流量和成分变化具有增强的鲁棒性。该研究为过程工业控制系统的设计提供了可操作的指导。
{"title":"Integrated Dynamic Simulation and Control Strategy Optimization in Rectisol Gas Purification Systems","authors":"Chao Ren, Peng Tian, Guochao Meng, Dongliang Chen, Assoc. Prof. Zhonglin Zhang, Prof. Xiaogang Hao","doi":"10.1002/ceat.70126","DOIUrl":"https://doi.org/10.1002/ceat.70126","url":null,"abstract":"<p>The Rectisol process plays a pivotal role in syngas purification for clean coal utilization. Feedstock variations during gasification induce syngas flow and composition fluctuations, necessitating adaptive process control. This study develops both proportional–integral–derivative (PID) and model predictive control (MPC) strategies for the CO<sub>2</sub> absorption column. The MPC controller was developed in MATLAB Simulink and innovatively integrated with Aspen Plus Dynamics through the AMSimulation interface module for co-simulation. The control strategies were evaluated under ±10 % flow and ±2 % CO<sub>2</sub> concentration disturbances, with purified gas quality assessed through response time (RT), overshoot (OS), and the integral of absolute error multiplied by time (ITAE). The data-driven MPC strategy exhibits enhanced robustness against flow and composition variations compared to conventional PID control. The study offers actionable guidance for control system design in process industries.</p>","PeriodicalId":10083,"journal":{"name":"Chemical Engineering & Technology","volume":"48 11","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145581006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}