DocumentCode
1164936
Title
A new filtering method for linear singularly perturbed systems
Author
Gajic, Z. ; Lim, M.T.
Author_Institution
Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
Volume
39
Issue
9
fYear
1994
fDate
9/1/1994 12:00:00 AM
Firstpage
1952
Lastpage
1955
Abstract
In this paper we present a new method which allows complete decomposition of the optimal global Kalman filter for linear singularly perturbed systems into pure-slow and pure-fast local optimal filters both driven by the system measurements. The method is based on the exact decomposition of the global singularly perturbed algebraic Riccati equation into pure-slow and pure-fast local algebraic Riccati equations. An F-8 aircraft example demonstrates the proposed method
Keywords
Kalman filters; filtering and prediction theory; perturbation techniques; F-8 aircraft; decomposition; linear singularly perturbed systems; local algebraic Riccati equations; optimal global Kalman filter; pure-fast local optimal filters; pure-slow local optimal filters; Aircraft; Communication channels; Coordinate measuring machines; Filtering theory; Gain measurement; Matrix decomposition; Noise measurement; Nonlinear filters; Riccati equations; Technological innovation;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.317133
Filename
317133
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