Robust Kalman Filtering: Asymptotic Analysis of the Least Favorable Model

被引：0

作者：

Zorzi, Mattia ^{[1
]}

Levy, Bernard C. ^{[2
]}

机构：

[1] Univ Padua, Dipartimento Ingn Informaz, Via Gradenigo 6-B, I-35131 Padua, Italy

[2] Univ Calif Davis, Dept Elect & Comp Engn, 1 Shields Ave, Davis, CA 95616 USA

来源：

2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2018年

关键词：

DISCRETE-TIME MATRIX; RICCATI EQUATION; CONVERGENCE;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider a robust filtering problem where the robust filter is designed according to the least favorable model belonging to a ball about the nominal model. In this approach, the ball radius specifies the modeling error tolerance and the least favorable model is computed by performing a Riccati-like backward recursion. We show that this recursion converges provided that the tolerance is sufficiently small.

引用

页码：7124 / 7129

页数：6

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