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<dc:title xml:lang="pl"><![CDATA[An interval Kalman filter enhanced by lowering the covariance matrix upper bound]]></dc:title>
<dc:creator><![CDATA[Tran, Tuan Anh]]></dc:creator>
<dc:creator><![CDATA[Jauberthie, Carine]]></dc:creator>
<dc:creator><![CDATA[Trave-Massuyés, Louise]]></dc:creator>
<dc:creator><![CDATA[Lu, Quoc Hung]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[uncertain linear systems]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[Kalman filters]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[interval analysis]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[estimation]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[covariance matrix]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[This paper proposes a variance upper bound based interval Kalman filter that enhances the interval Kalman filter based on the same principle proposed by Tran et al. (2017) for uncertain discrete time linear models. The systems under consideration are subject to bounded parameter uncertainties not only in the state and observation matrices, but also in the covariance matrices of the Gaussian noises.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[By using the spectral decomposition of a symmetric matrix and by optimizing the gain matrix of the proposed filter, we lower the minimal upper bound on the state estimation error covariance for all admissible uncertainties. This paper contributes with an improved algorithm that provides a less conservative error covariance upper bound than the approach proposed by Tran et al. (2017). The state estimates are determined using interval analysis in order to enclose the set of all possible solutions of the classical Kalman filter consistent with the uncertainties.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Korbicz, Józef (1951- ) - red.]]></dc:contributor>
<dc:contributor><![CDATA[Uciński, Dariusz - red.]]></dc:contributor>
<dc:date><![CDATA[2021]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/86261/AMCS_2021_31_2_6.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/101353/edition/86261/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:86261]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 31, number 2 (2021)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=120]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:101353]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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