Kalman filtering design on systems with Markovian jump parameters

Author

Shi, Yan ; Shi, Peng

Author_Institution

Dept. of Inf. & Syst. Eng., Kyushu Tokai Univ., Kumamoto, Japan

Volume

1

fYear

2000

fDate

2000

Firstpage

450

Abstract

This paper studies the problem of Kalman filtering for a class of uncertain linear continuous-time systems with Markovian jumping parameters. The system under consideration is subjected to time-varying norm-bounded parameter uncertainties in the state and measurement equations. Stochastic quadratic stability of the above system is analyzed. A state estimator is designed such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties, which is in terms of solutions of two sets of coupled algebraic Riccati equations

Keywords

Kalman filters; Markov processes; Riccati equations; continuous time systems; filtering theory; stability; state estimation; time-varying systems; uncertain systems; Kalman filtering design; Markovian jump parameters; coupled algebraic Riccati equations; estimation error covariance; measurement equations; state equations; state estimator; stochastic quadratic stability; time-varying norm-bounded parameter uncertainties; uncertain linear continuous-time systems; Estimation error; Filtering; Kalman filters; Nonlinear filters; Riccati equations; Stability analysis; State estimation; Stochastic systems; Time varying systems; Uncertain systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-5747-7

Type

conf

DOI

10.1109/ICOSP.2000.894529

Filename

894529