Formulation of Economic Model Predictive Control to Address System Dynamics over Multiple Time Scales

被引:0
|
作者
Ellis, Matthew J. [1 ]
机构
[1] Univ Calif Davis, Dept Chem Engn, Davis, CA 95616 USA
来源
2020 AMERICAN CONTROL CONFERENCE (ACC) | 2020年
关键词
D O I
10.23919/acc45564.2020.9147829
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a composite model predictive control (MPC) structure for the class of standard singularly perturbed systems is developed. To control and optimize economic performance of the slow dynamics, an economic MPC is developed and to stabilize the fast dynamics, a fast MPC is designed. Both MPC strategies do not rely on explicit stabilizing and/or terminal constraints. Working within a sampled-data setting, closed-loop stability in the sense of asymptotic stability of the economically optimal steady state is discussed. A chemical process example is given to demonstrate the control architecture.
引用
收藏
页码:1974 / 1979
页数:6
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