Model validation and state estimation for uncertain continuous-time systems with missing discrete-continuous data

Author

Savkin, Andrey V. ; Petersen, Ian R.

Author_Institution

Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia

Volume

1

fYear

1996

fDate

11-13 Dec 1996

Firstpage

570

Abstract

This paper considers two related problems of state estimation and model validation for a class of uncertain linear systems. The main contribution of the paper is that it considers a general information structure which allows for discrete and continuous measurements as well as missing data. The results are given in terms of a recursive state estimator involving a jump Riccati differential equation and jump state equations. These equations can be solved online

Keywords

Riccati equations; nonlinear differential equations; recursive estimation; state estimation; uncertain systems; continuous measurements; discrete measurements; information structure; jump Riccati differential equation; jump state equations; missing discrete-continuous data; model validation; recursive state estimator; state estimation; uncertain continuous-time systems; Differential equations; Filtering; Integral equations; Kalman filters; Linear systems; Riccati equations; Robustness; State estimation; Uncertain systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.574381

Filename

574381