DocumentCode :
2159417
Title :
Minimax filter for statistically uncertain stochastic discrete-continuous linear system
Author :
Miller, Gregory ; Pankov, Alexey ; Siemenikhin, Konstantin
Author_Institution :
Probability Theor. Dept., Moscow Aviation Inst., Moscow, Russia
fYear :
2007
fDate :
2-5 July 2007
Firstpage :
3926
Lastpage :
3933
Abstract :
A linear stochastic system with continuous dynamics is considered with two types of observations: purely discrete and discrete-continuous. It is assumed that the intensities of noises are uncertain and belong to a given and known a priori uncertainty set. The problem is stated as a minimax one with respect to integral mean-square optimization criterion. The optimal minimax filter is presented in the form of explicit equations depending on the solution of the corresponding dual optimization problem. For the computation of the dual problem solution an effective iterative procedure is provided and its convergence is proved.
Keywords :
continuous systems; convergence; discrete systems; filtering theory; integral equations; iterative methods; linear systems; mean square error methods; optimisation; stochastic systems; uncertain systems; continuous dynamics; convergence; discrete system; discrete-continuous system; dual optimization problem; explicit equation; integral mean-square optimization criterion; iterative procedure; linear stochastic system; optimal minimax filter; statistically uncertain stochastic discrete-continuous linear system; Differential equations; Equations; Mathematical model; Noise; Optimization; Stochastic processes; Uncertainty; dual problem; linear stochastic system; minimax filtering; uncertainty set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (ECC), 2007 European
Conference_Location :
Kos
Print_ISBN :
978-3-9524173-8-6
Type :
conf
Filename :
7068493
Link To Document :
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