Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

Myung Gon Yoon; Valery A. Ugrinovskii; Ian R. Petersen

Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

Myung Gon Yoon^*
, Valery A. Ugrinovskii
, Ian R. Petersen

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

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 LEQG control. The structure and properties of the resulting filter are analyzed and compared to H_∞ and Kalman filters.

Original language	English
Pages (from-to)	610-615
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	1
Publication status	Published - 2002
Externally published	Yes
Event	41st IEEE Conference on Decision and Control - Las Vegas, NV, United States Duration: 10 Dec 2002 → 13 Dec 2002

Cite this

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title = "Robust finite horizon minimax filtering for discrete time stochastic uncertain systems",

abstract = "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 LEQG control. The structure and properties of the resulting filter are analyzed and compared to H∞ and Kalman filters.",

author = "Yoon, \{Myung Gon\} and Ugrinovskii, \{Valery A.\} and Petersen, \{Ian R.\}",

year = "2002",

language = "English",

volume = "1",

pages = "610--615",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "41st IEEE Conference on Decision and Control ; Conference date: 10-12-2002 Through 13-12-2002",

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TY - JOUR

T1 - Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

AU - Yoon, Myung Gon

AU - Ugrinovskii, Valery A.

AU - Petersen, Ian R.

PY - 2002

Y1 - 2002

N2 - 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 LEQG control. The structure and properties of the resulting filter are analyzed and compared to H∞ and Kalman filters.

AB - 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 LEQG control. The structure and properties of the resulting filter are analyzed and compared to H∞ and Kalman filters.

UR - https://www.scopus.com/pages/publications/0036993505

M3 - Conference article

AN - SCOPUS:0036993505

SN - 0191-2216

VL - 1

SP - 610

EP - 615

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - 41st IEEE Conference on Decision and Control

Y2 - 10 December 2002 through 13 December 2002

ER -

Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

Abstract

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