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Robust finite horizon minimax filtering for discrete time stochastic uncertain systems

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dc.contributor.authorYoon, Myung Gonen
dc.contributor.authorUgrinovskii, Valery A.en
dc.contributor.authorPetersen, Ian R.en
dc.date.accessioned2026-06-28T20:41:54Z
dc.date.available2026-06-28T20:41:54Z
dc.date.issued2002en
dc.description.abstractWe 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.en
dc.description.sponsorshipThis work was supported by The Australian Research Council.en
dc.description.statusPeer-revieweden
dc.format.extent6en
dc.identifier.issn0191-2216en
dc.identifier.otherORCID:/0000-0003-4856-9450/work/218841667en
dc.identifier.scopus0036993505en
dc.identifier.urihttps://hdl.handle.net/1885/733812202
dc.language.isoenen
dc.relation.ispartofseries41st IEEE Conference on Decision and Controlen
dc.sourceProceedings of the IEEE Conference on Decision and Controlen
dc.titleRobust finite horizon minimax filtering for discrete time stochastic uncertain systemsen
dc.typeConference paperen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage615en
local.bibliographicCitation.startpage610en
local.contributor.affiliationYoon, Myung Gon; University of New South Walesen
local.contributor.affiliationUgrinovskii, Valery A.; University of New South Walesen
local.contributor.affiliationPetersen, Ian R.; School of Electrical Engineeringen
local.identifier.citationvolume1en
local.identifier.pure9d2675d2-7b7a-46f4-8077-c45d3db21dbaen
local.identifier.urlhttps://www.scopus.com/pages/publications/0036993505en
local.type.statusPublisheden

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