On applicability of the interacting multiple-model approach to state estimation for systems with sojourn-time-dependent Markov model switching

Author

Petrov, A.I. ; Zubov, A.G.

Author_Institution

Dept. of Autom. Control Syst., Moscow Aviation Inst., Moscow, Russia

Volume

41

Issue

1

fYear

1996

fDate

1/1/1996 12:00:00 AM

Firstpage

136

Lastpage

140

Abstract

In this paper the attempt at the interacting multiple-model (IMM) method extension to the state estimation problem with semi-Markov [sojourn-time-dependent Markov (STDM)] system model switching is analyzed. It is demonstrated that such an STDM-IMM approach does not properly take into account the specific character of the STDM switching in the system, and it becomes a reason for the reduction of estimation accuracy. For this problem it is shown that a hypotheses merging should be restricted in such a way that not only the current system model, but also the sojourn time in the model, should be given in hypotheses to be tested. Some other aspects of Bayesian estimation in a switching environment are also discussed

Keywords

Bayes methods; Markov processes; linear systems; probability; state estimation; Bayesian estimation; estimation accuracy; interacting multiple-model; linear systems; probability; sojourn-time-dependent Markov model switching; state estimation; Artificial intelligence; Bayesian methods; Eigenvalues and eigenfunctions; History; Merging; Robust stability; State estimation; Sufficient conditions; Symmetric matrices; Uncertain systems;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.481619

Filename

481619