Robust state estimation for uncertain systems with averaged integral quadratic constraints

被引：4
|
作者：
Savkin, AV
Petersen, IR
机构：
[1] UNIV MELBOURNE,COOPERAT RES CTR SENSOR SIGNAL & INFORMAT PROC,PARKVILLE,VIC 3052,AUSTRALIA
[2] AUSTRALIAN DEF FORCE ACAD,DEPT ELECT ENGN,CAMPBELL,ACT 2600,AUSTRALIA
来源：
INTERNATIONAL JOURNAL OF CONTROL | 1996年 / 64卷 / 05期
基金：
澳大利亚研究理事会;
关键词：
D O I：
10.1080/00207179608921665
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 considers a robust state estimation problem for a new class of uncertain systems. The new uncertainty class introduced in the paper involves structured uncertainties which are required to satisfy a certain averaged integral quadratic constraint. This uncertainty class combines aspects of norm-bounded and stochastic uncertainty descriptions. The solution to the robust state estimation problem is obtained by solving a parametrized Riccati differential equation of the game type.
引用
收藏
页码：923 / 939
页数：17
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