Game theory approach to state estimation of linear discrete-time processes and its relation toH∞-optimal estimation

DOI10.1080/00207179208934293zbMath0774.93028OpenAlexW1997618097MaRDI QIDQ4013286

Isaac Yaesh, Uri Shaked

Publication date: 27 September 1992

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179208934293

zbMATH Keywords

Riccati equationerror covariance matrix\(H^ \infty\) optimizationlinear quadratic game theory

Mathematics Subject Classification ID

Applications of game theory (91A80) Estimation and detection in stochastic control theory (93E10) (H^infty)-control (93B36)

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On Pareto set in control and filtering problems under stochastic and deterministic disturbances ⋮ Cubature \(H_\infty\) information filter and its extensions ⋮ Transient and asymptotic analysis of discrete-time \(H_\infty\)-filters ⋮ Discrete-time minmax filtering subject to a norm-constrained state estimate ⋮ Optimal discrete-timeH_∞/γ₀filtering and control under unknown covariances ⋮ A cubatureH_∞filter and its square-root version ⋮ \(H_{\infty}\) estimation for fuzzy membership function optimization

Cites Work

• On a minimax estimate for the mean of a normal random vector under a generalized quadratic loss function
• State-space solutions to standard H/sub 2/ and H/sub infinity / control problems
• H/sub infinity /-minimum error state estimation of linear stationary processes
• The Kalman filter: A robust estimator for some classes of linear quadratic problems