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Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

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3 Author(s)
Myung-Gon Yoon ; Sch. of Electr. Eng., Australian Defence Force Acad., Canberra, ACT, Australia ; Ugrinovskii, V.A. ; Petersen, I.R.

We study a finite-horizon robust minimax filtering problem for time-varying discrete-time stochastic uncertain systems. The uncertainty in the system is characterized by a set of probability measures under which the stochastic noises, driving the system, are defined. The optimal minimax filter has been found by applying techniques of risk-sensitive linear-quadratic exponential Gaussian (LEQG) control. The structure and properties of the resulting filter are analyzed and compared to H and Kalman filters.

Published in:

Decision and Control, 2002, Proceedings of the 41st IEEE Conference on  (Volume:1 )

Date of Conference:

10-13 Dec. 2002

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