DocumentCode
3161327
Title
A distributed Kalman filter for actuator fault estimation of deep space formation flying satellites
Author
Azizi, S.M. ; Khorasani, K.
Author_Institution
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, QC
fYear
2009
fDate
23-26 March 2009
Firstpage
354
Lastpage
359
Abstract
In this paper, a new distributed Kalman filter scheme is proposed to estimate actuator faults for deep space formation flying satellites. The method can also be applied to large-scale systems such as sensor networks and power systems. For a hierarchical large-scale system, the overlapping block-diagonal state space (OBDSS) representation of the system is transformed into our proposed constrained-state block-diagonal state space (CSBDSS) model. The proposed model becomes purely diagonal which simplifies and allows the distributed implementation of the Kalman filters. The constrained-state condition needs to be satisfied at each Kalman filtering iteration which is shown to be equivalent to solving local constrained optimization cost functions. Simulation results presented confirm the effectiveness of our proposed analytical work.
Keywords
Kalman filters; actuators; artificial satellites; hierarchical systems; large-scale systems; state-space methods; Kalman filtering iteration; actuator fault estimation; constrained-state block-diagonal state space model; cost functions; deep space formation flying satellites; distributed Kalman filter; hierarchical large-scale systems; overlapping block-diagonal state space representation; power systems; sensor networks; Actuators; Constraint optimization; Filtering; Kalman filters; Large-scale systems; Power system faults; Power system modeling; Satellites; Sensor systems; State-space methods; Deep Space; Distributed; Formation Flying; Kalman Filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems Conference, 2009 3rd Annual IEEE
Conference_Location
Vancouver, BC
Print_ISBN
978-1-4244-3462-6
Electronic_ISBN
978-1-4244-3463-3
Type
conf
DOI
10.1109/SYSTEMS.2009.4815826
Filename
4815826
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