scholarly journals Kalman filtering and Riccati equations for descriptor systems

1992 ◽  
Vol 37 (9) ◽  
pp. 1325-1342 ◽  
Author(s):  
R. Nikoukhah ◽  
A.S. Willsky ◽  
B.C. Levy
1991 ◽  
Author(s):  
Ramine Nikoukhah ◽  
Alan S. Willsky ◽  
Bernard C. Levy

1992 ◽  
Vol 19 (4) ◽  
pp. 325-334 ◽  
Author(s):  
L. Chisci ◽  
G. Zappa

2013 ◽  
Vol 734-737 ◽  
pp. 3186-3189
Author(s):  
Shu Fen Wang ◽  
Ying Shi

A robust Kalman-type recursive filter has been proposed for descriptor systems subject to linear unstructured additive uncertainties in this paper. It is proved that the linear additive uncertainties during filtering can be represented by the intersection of a series of additive uncertainties relying on the actual plant. A set of additive uncertainties independent of the actual states is utilized in this paper to include this intersection, whose parameters can be obtained offline through convex optimizations. A numerical simulation shows that the algorithm can be realized recursively for linear additive uncertain-ties, and verifies the effectiveness of the proposed algorithm.


2012 ◽  
Vol 433-440 ◽  
pp. 3601-3607
Author(s):  
Hang Wei Tian ◽  
Ying Shi

Based on the classical Kalman filtering theory, the state estimation problem is considered for non-square descriptor discrete time stochastic systems. Under Assumptions 1~3, a fixed-Interval Kalman smoother for non-square descriptor systems with correlated noise is given. Some numerical examples illustrate the effectiveness of the proposed algorithm.


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