Robust model predictive control of constrained linear systems with bounded disturbances

被引：1174

作者：

Mayne, DQ ^{[1
]}

Seron, MM

Rakovic, SV

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, London SW7 2BT, England

[2] Univ Newcastle, Sch Elect Engn & Comp Sci, Newcastle, NSW 2308, Australia

来源：

AUTOMATICA | 2005年 / 41卷 / 02期

基金：

英国工程与自然科学研究理事会;

关键词：

robust model predictive control; robustness; bounded disturbances;

D O I：

10.1016/j.automatica.2004.08.019

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 provides a novel solution to the problem of robust model predictive control of constrained, linear, discrete-time systems in the presence of bounded disturbances. The optimal control problem that is solved online includes, uniquely, the initial state of the model employed in the problem as a decision variable. The associated value function is zero in a disturbance invariant set that serves as the 'origin' when bounded disturbances are present, and permits a strong stability result, namely robust exponential stability of the disturbance invariant set for the controlled system with bounded disturbances, to be obtained. The resultant online algorithm is a quadratic program of similar complexity to that required in conventional model predictive control. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：219 / 224

页数：6

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