Model predictive control of nonlinear singularly perturbed systems: Application to a large-scale process network

被引：41
|
作者：
Chen, Xianzhong [1 ]
Heidarinejad, Mohsen [2 ]
Liu, Jinfeng [1 ]
Munoz de la Pena, David [3 ]
Christofides, Panagiotis D. [1 ,2 ]
机构：
[1] Univ Calif Los Angeles, Dept Chem & Biomol Engn, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
[3] Univ Seville, Dept Ingn Sistemas & Automat, Seville 41092, Spain
来源：
JOURNAL OF PROCESS CONTROL | 2011年 / 21卷 / 09期
关键词：
Two-time-scale processes; Model predictive control; Distributed predictive control; Nonlinear processes; ARCHITECTURES; STATE;
D O I：
10.1016/j.jprocont.2011.07.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This work focuses on model predictive control of nonlinear singularly perturbed systems. A composite control system using multirate sampling (i.e., fast sampling of the fast state variables and slow sampling of the slow state variables) and consisting of a "fast" feedback controller that stabilizes the fast dynamics and a model predictive controller that stabilizes the slow dynamics and enforces desired performance objectives in the slow subsystem is designed. Using stability results for nonlinear singularly perturbed systems, the closed-loop system is analyzed and sufficient conditions for stability are derived. A large-scale nonlinear reactor-separator process network which exhibits two-time-scale behavior is used to demonstrate the controller design including a distributed implementation of the predictive controller. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1296 / 1305
页数：10
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