A key feature of amine-based post-combustion CO₂ capture process is a wide operating range induced by periodic load changes in power plants, which necessitates flexible operation. One possible approach to enhance the operational flexibility is to design a reliable controller that can effectively regulate the process over the operating range. To this end, in this study, a robust model predictive controller is designed by analyzing the dynamic characteristics of a post-combustion CO₂ capture process. Specifically, gap metric analysis is performed to analyze the sensitivity of the process. From this analysis, optimal operating conditions are identified by evaluating similarity among the dynamics around different operating conditions. Then, a single linear model predictive controller is designed on the basis of the linear approximation of the original nonlinear model at the chosen conditions. Finally, the effectiveness of the controller is illustrated through a case study on an example CO₂ capture process.

胺基燃烧后CO ₂捕集过程的关键特征是发电厂周期性负载变化引起的宽工作范围，因此需要灵活的操作。一种提高操作灵活性的可能方法是设计一种可靠的控制器，该控制器可以在整个操作范围内有效地调节过程。为此，在本研究中，通过分析燃烧后CO ₂的动态特性来设计鲁棒模型预测控制器。捕获过程。具体而言，执行间隙度量分析以分析过程的敏感性。通过该分析，可以通过评估不同工况周围动态之间的相似性来确定最佳工况。然后，在选定条件下，基于原始非线性模型的线性逼近，设计了一个线性模型预测控制器。最后，通过对一个示例性CO ₂捕获过程的案例研究来说明控制器的有效性。