A synthesis approach for output feedback robust constrained model predictive control

被引：124

作者：

Ding, Baocang ^{[1
]}

Xi, Yugeng ^{[2
]}

Cychowski, Marcin T. ^{[3
]}

O'Mahony, Thomas ^{[3
]}

机构：

[1] Chongqing Univ, Coll Automat, Chongqing 400030, Peoples R China

[2] Shanghai Jiao Tong Univ, Inst Automat, Shanghai 200240, Peoples R China

[3] Cork Inst Technol, Adv Control Grp, Cork, Ireland

来源：

AUTOMATICA | 2008年 / 44卷 / 01期

基金：

中国国家自然科学基金;

关键词：

robust model predictive control; output feedback; state estimator; constraint;

D O I：

10.1016/j.automatica.2007.04.005

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 paper addresses the synthesis approach for output feedback robust model predictive control for systems with polytopic description, bounded state disturbance and measurement noise. Off-line, it calculates a sequence of output feedback laws based on the state estimators, by solving linear matrix inequality (LMI) optimization problems. On-line, at each sampling time, it chooses an appropriate output feedback law from this sequence. The primary contribution is to present a rigorous method to guarantee satisfaction of input/state constraints. A numerical example is given to illustrate the effectiveness of the controller. (c) 2007 Elsevier Ltd. All rights reserved.

引用

页码：258 / 264

页数：7

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