文章基本信息

标题：Advanced Modeling and Control of a Solid Sorbent-Based CO2 Capture Process
本地全文：下载
作者：Benjamin P. Omell ; Jinliang Ma ; Priyadarshi Mahapatra 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：633-638
DOI：10.1016/j.ifacol.2016.07.240
语种：English
出版社：Elsevier
摘要：Solid sorbent-based CO2 capture from flue gas provides a novel alternative to traditional solvent-based processes due to potentially lower energy consumption for regeneration. Optimal operation of such a gas-solid flow process requires an advanced control framework for efficient disturbance rejection and setpoint tracking. This work focuses on the development of computationally fast and accurate dynamic reduced models (D-RMs) and the application of these models to nonlinear model predictive control (NMPC) algorithms. Two different types of D-RMs are developed: the first type is a data-driven model where step-test data are utilized to generate the D-RM through the Decoupled A-B Net (DABNet) model, and the second type of D-RM is a temporal and spatial reduction of the original process model to improve its computational efficiency while still retaining its physics. Disturbance rejection and setpoint tracking characteristics of the NMPC and its computational performance are studied for both types of D-RMs. In addition, performance of both NMPC formulations are compared with linear model predictive control (LMPC) formulations.
关键词：Reduced-order modelsnonlinear model predictive controlcontrolCO2 capture