Piecewise affinity of min-max MPC with bounded additive uncertainties and a quadratic criterion

被引：19
|
作者：
Ramirez, DR [1 ]
Camacho, EF [1 ]
机构：
[1] Univ Seville, Dept Ingn Sistemas & Automat, Escuela Super Ingn, Seville 41092, Spain
来源：
AUTOMATICA | 2006年 / 42卷 / 02期
关键词：
min-max MPC algorithm; predictive control; min-max optimization; piecewise linear controllers; uncertainty;
D O I：
10.1016/j.automatica.2005.09.009
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 brief shows how a min-max MPC with bounded additive uncertainties and a quadratic cost function results in a piecewise affine and continuous control law. Proofs based on properties of the cost function and the optimization problem are given. The boundaries of the regions in which the state space can be partitioned are also treated. The results are illustrated by an example. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：295 / 302
页数：8
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