Game Theory Approach to Optimal Linear State Estimation and Its Relation to the Minimum H-Norm Estimation

I. Yaesh; U. Shaked

doi:10.1109/9.256343

Game Theory Approach to Optimal Linear State Estimation and Its Relation to the Minimum H-Norm Estimation

I. Yaesh, U. Shaked

School of Electrical Engineering

Tel Aviv University

Research output: Contribution to journal › Article › peer-review

54 Scopus citations

Abstract

A possible game theory approach to optimal state estimation is presented. It is found that in a certain differential game, the minimizer's policy is identical to the one obtained by optimal estimation in the minimum H,-norm sense. This interpretation of the H-optimal state estimation provides a better insight into the mechanism of the -optimal filtering, especially, in the case where the exogenous signals are not energy bounded.

Original language	English
Pages (from-to)	828-831
Number of pages	4
Journal	IEEE Transactions on Automatic Control
Volume	37
Issue number	6
DOIs	https://doi.org/10.1109/9.256343
State	Published - Jun 1992

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abstract = "A possible game theory approach to optimal state estimation is presented. It is found that in a certain differential game, the minimizer's policy is identical to the one obtained by optimal estimation in the minimum H,-norm sense. This interpretation of the H-optimal state estimation provides a better insight into the mechanism of the -optimal filtering, especially, in the case where the exogenous signals are not energy bounded.",

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Game Theory Approach to Optimal Linear State Estimation and Its Relation to the Minimum H-Norm Estimation

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