DocumentCode
619952
Title
Optimal Kalman filtering for systems with unknown inputs
Author
Lingchen Ren ; Yingting Luo
Author_Institution
Coll. of Math., Sichuan Univ., Chengdu, China
fYear
2013
fDate
25-27 May 2013
Firstpage
1580
Lastpage
1583
Abstract
In this paper, we consider the state estimation for dynamic system with unknown inputs by difference method. We proposed an optimal algorithm in mean square error sense. The new algorithm shows good performance with less computations compared to that of traditional algorithms. Moreover, numerical examples show that the new algorithm still works well even with the wrong initial value of unknown inputs.
Keywords
Kalman filters; mean square error methods; state estimation; difference method; dynamic system; mean square error sense; optimal Kalman filtering; optimal algorithm; state estimation; unknown inputs; Decision support systems; TV; ASKF; Optimal estimate; TSKF; difference method; unknown inputs;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location
Guiyang
Print_ISBN
978-1-4673-5533-9
Type
conf
DOI
10.1109/CCDC.2013.6561181
Filename
6561181
Link To Document