On stochastic filtering approximations of estimation problems for systems with uncertainty∗

Kurzhanski, A. (1988). On stochastic filtering approximations of estimation problems for systems with uncertainty∗. Stochastics 23 (2) 109-130. 10.1080/17442508808833485.

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Abstract

This paper considers estimating the state of a discrete-time linear system in which the values of an unobserved disturbance process are only known to lie in certain prescribed sets. By introducing additional stochastic disturbances it is shown that this problem can be approximated to arbitrarily high accuracy by the solution of a Kalman filtering problem

Item Type:	Article
Uncontrolled Keywords:	State estimation, multistage linear system, geometric constraints, convex analysis, Kalman filter
Depositing User:	Romeo Molina
Date Deposited:	14 Dec 2016 10:28
Last Modified:	27 Aug 2021 17:41
URI:	https://pure.iiasa.ac.at/14150

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