Toward a Unifying Framework Blending Real-Time Optimization and Economic Model Predictive Control

被引:16
|
作者
Faulwasser, Timm [1 ]
Pannocchia, Gabriele [2 ]
机构
[1] KIT, Inst Automat & Appl Informat, D-76131 Karlsruhe, Germany
[2] Univ Pisa, Chem Engn Sect, Dept Civil & Ind Engn, I-56122 Pisa, Italy
关键词
MODIFIER-ADAPTATION METHODOLOGY; SET-POINT OPTIMIZATION; SYSTEM OPTIMIZATION; TURNPIKE; MPC; PERFORMANCE; ALGORITHM; OPERATION; DISSIPATIVITY; FORMULATION;
D O I
10.1021/acs.iecr.9b00782
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Nowadays, real-time optimization (RTO) and nonlinear as well as linear model predictive control (MPC) are standard methods in operation and process control systems. Hence there exists a good understanding of how to combine RTO and set point tracking MPC schemes. However, recently, there has been substantial progress in analyzing the properties of so-called economic MPC schemes. This paper proposes a conceptual framework to blend ideas from (output) modifier adaptation and offset-free economic MPC with recent results on economic MPC without terminal constraints. Specifically, we leverage recent insights into economic MPC based on turnpike and dissipativity properties of the underlying optimal control problem. Interestingly, the proposed scheme alleviates the need for a dedicated computation of steady-state targets by exploiting the turnpike property in the open-loop predictions. Two detailed simulation examples show that the proposed schemes deliver excellent performance, while being conceptually much simpler.
引用
收藏
页码:13583 / 13598
页数:16
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