Filtering for bimodal systems: the case of unknown switching statistics

Author

Germani, Alfredo ; Manes, Costanzo ; Palumbo, Pasquale

Author_Institution

Dipt. di Ingegneria Elettrica e dell´´Informazione, Universita degli Studi dell´´Aquila, L´´Aquila

Volume

53

Issue

6

fYear

2006

fDate

6/1/2006 12:00:00 AM

Firstpage

1266

Lastpage

1277

Abstract

This paper considers the problem of state estimation for discrete-time systems whose dynamics randomly switches between two linear stochastic behaviors (bimodal systems). The novelty of this paper is that no statistical information on the switching process is assumed available for the filter design. Two different approaches are here proposed to solve the estimation problem in these conditions. One method is based on a combined use of stochastic singular systems and of the minimax filtering theory, while the other relies on the maximum entropy principle. Based on these approaches two filtering algorithms are derived, whose features are theoretically and numerically compared. Some attention has been devoted to the study of the asymptotic properties of both the filters

Keywords

discrete time filters; filtering theory; maximum entropy methods; statistical analysis; bimodal systems; discrete-time systems; filter design; linear stochastic behaviors; maximum entropy principle; minimax filtering theory; state estimation; statistical information; stochastic singular systems; switching process; unknown switching statistics; Entropy; Filtering algorithms; Filtering theory; Information filtering; Information filters; Minimax techniques; State estimation; Statistics; Stochastic systems; Switches; Fault diagnosis; Markovian jump systems; filtering theory; stochastic systems; switched systems;

fLanguage

English

Journal_Title

Circuits and Systems I: Regular Papers, IEEE Transactions on

Publisher

ieee

ISSN

1549-8328

Type

jour

DOI

10.1109/TCSI.2006.870542

Filename

1643433