Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

Thumbnail Image

Date

2002

Authors

Yoon, Myung Gon
Ugrinovskii, Valery A.
Petersen, Ian R.

Journal Title

Journal ISSN

Volume Title

Publisher

Access Statement

Research Projects

Organizational Units

Journal Issue

Abstract

We study a finite-horizon robust minimax filtering problem for time-varying discrete-time stochastic uncertain systems. The uncertainty in the system is characterized by a set of probability measures under which the stochastic noises, driving the system, are defined. The optimal minimax filter has been found by applying techniques of risk-sensitive LEQG control. The structure and properties of the resulting filter are analyzed and compared to H∞ and Kalman filters.

Description

Keywords

Citation

URI

https://hdl.handle.net/1885/733812202

Collections

ANU Research Publications

Source

Proceedings of the IEEE Conference on Decision and Control

Type

Conference paper

Book Title

Entity type

Publication

Access Statement

License Rights

DOI

Restricted until

DSpace software copyright © 2002-2026 LYRASIS