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
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
收藏
页码:1038 / 1048
页数:11
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