A new suboptimal approach to the filtering problem for bilinear stochastic differential systems

被引：0

作者：

Carravetta, F ^{[1
]}

Germani, A ^{[1
]}

Shuakayev, MK ^{[1
]}

机构：

[1] CNR, Ist Anal Sistemi & Informat, I-00185 Rome, Italy

来源：

PROCEEDINGS OF THE 39TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5 | 2000年

关键词：

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：

The aim of this paper is to present a new approach to the filtering problem for the class of bilinear stochastic multivariable systems, consisting in searching for suboptimal state-estimates instead of the conditional statistics. As a first result, a finite-dimensional optimal linear filter for the considered class of systems is defined. Then, the more general problem of designing polynomial finite-dimensional filters is considered. The equations of a finite-dimensional filter are given, producing a state-estimate which is optimal in a class of polynomial transformations of the measurements with arbitrarily fixed degree. Numerical simulations show the effectiveness of the proposed filter.

引用

页码：4264 / 4269

页数：6

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