Off-line approach to dynamic output feedback robust model predictive control

被引：37

作者：

Ping, Xubin ^{[1
]}

Ding, Baocang ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Minist Educ, Key Lab Intelligent Networks & Network Secur MOE, Sch Elect & Informat Engn,Dept Automat, Xian 710049, Peoples R China

来源：

SYSTEMS & CONTROL LETTERS | 2013年 / 62卷 / 11期

关键词：

Output feedback; Model predictive control; Uncertain systems; Off-line approach; SYSTEMS; MPC; PERFORMANCE; STABILITY;

D O I：

10.1016/j.sysconle.2013.07.011

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 presents an off-line approach to the dynamic output feedback robust model predictive control (OFRMPC) for a system with both polytopic uncertainty and bounded disturbance. For the off-line optimization, a sequence of controller parameters and the corresponding regions of attraction are calculated for all combinations of the pre-specified estimated states and estimation error sets (EESs). These controller parameters and the corresponding regions of attraction are stored in a look-up table. On-line, the controller parameters are searched in this look-up table corresponding to real-time EES, and to the region of attraction with the closest containment of real-time estimated state. This method considerably reduces the on-line computational burden. Two numerical examples are given to illustrate the effectiveness of the approach. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：1038 / 1048

页数：11

共 29 条

[1] Design of state estimators for uncertain linear systems using quadratic boundedness [J].