DocumentCode
289760
Title
Sensitivity analysis of linear optimal stochastic observers
Author
Madjarov, Nikola ; Mihaylova, Ludmila
Author_Institution
Dept. of Autom., Tech. Univ. Sofia, Bulgaria
fYear
1993
fDate
17-20 Oct 1993
Firstpage
482
Abstract
The paper considers the continuous-time and discrete-time Kalman filters under noise uncertainties. The influence of these uncertainties on the filter performance can be characterized by the so-called sensitivity functions. Different ways for defining sensitivity functions are proposed and relationships for the corresponding functions are derived with the aid of matrix derivatives and finite differences. The results are illustrated with examples
Keywords
Kalman filters; Riccati equations; continuous time filters; discrete time filters; observers; sensitivity analysis; continuous-time Kalman filters; discrete-time Kalman filters; finite differences; linear optimal stochastic observers; matrix derivatives; noise uncertainties; sensitivity analysis; sensitivity functions; Covariance matrix; Estimation error; Filtering algorithms; Kalman filters; Mathematical model; Riccati equations; Sensitivity analysis; State estimation; Stochastic processes; Uncertain systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
Conference_Location
Le Touquet
Print_ISBN
0-7803-0911-1
Type
conf
DOI
10.1109/ICSMC.1993.384919
Filename
384919
Link To Document