文章基本信息

标题：Economic NMPC Strategies for Solid Sorbent-Based CO 2 Capture
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作者：Mingzhao Yu ; Lorenz T. Biegler
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：18
页码：103-108
DOI：10.1016/j.ifacol.2018.09.283
语种：English
出版社：Elsevier
摘要：AbstractNonlinear Model Predictive Control (NMPC) enables the incorporation of detailed dynamic process models for nonlinear, multivariable control with constraints. This optimization-based framework also leads to on-line dynamic optimization with performance-based and so-called economic objectives. Nevertheless, economic NMPC (eNMPC) still requires careful formulation of the nonlinear programming (NLP) subproblem to guarantee stability. In this study, we derive a novel reduced regularization approach for eNMPC with stability guarantees. The resulting eNMPC framework is applied to a challenging nonlinearCO2capture model, where bubbling fluidized bed models comprise a solid-sorbent post-combustion carbon capture system. Our results indicate the benefits of this improved eNMPC approach over tracking to the setpoint, and better stability over eNMPC without regularization.
关键词：Keywordsnonlinear model predictive controleconomic NMPCbubbling fluidized bedCO2capturenonlinear optimization