Robust model predictive control of constrained linear systems with bounded disturbances

被引：1071
|
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.
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页码：219 / 224
页数：6
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