Fuzzy Kalman Filter using Linear Matrix Inequalities

dc.contributor.authorHanna Aboukheir
dc.contributor.authorMarco Herrera
dc.contributor.authorEdinzo Iglesias
dc.contributor.authorÓscar Camacho
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:30:43Z
dc.date.available2026-03-22T15:30:43Z
dc.date.issued2021
dc.descriptionCitaciones: 2
dc.description.abstractThe Kalman filter has been extensively used in different applications due to its strengths in estimating the system states under noisy observations. In this paper, a modification of the classical Kalman filter for nonlinear state estimation is presented; firstly, a polytopic set of linear discrete-time models based on a Takagi-Sugeno inference system is used to describe the nonlinear operating region. The stabilizing gains of the linear filters are calculated using Linear Matrix Inequalities (LMI), the proposal is evaluated through simulations.
dc.identifier.doi10.1109/chilecon54041.2021.9703045
dc.identifier.urihttps://doi.org/10.1109/chilecon54041.2021.9703045
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/52794
dc.language.isoen
dc.relation.ispartof2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)
dc.sourceNational Archives of Ecuador
dc.subjectKalman filter
dc.subjectControl theory (sociology)
dc.subjectAlpha beta filter
dc.subjectInvariant extended Kalman filter
dc.subjectLinear matrix inequality
dc.subjectFast Kalman filter
dc.subjectEnsemble Kalman filter
dc.subjectNonlinear system
dc.subjectMathematics
dc.subjectFilter (signal processing)
dc.titleFuzzy Kalman Filter using Linear Matrix Inequalities
dc.typearticle

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