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An Adaptive Formulation of the Sliding Innovation Filter

dc.contributor.authorLee AS
dc.contributor.authorGadsden SA
dc.contributor.authorAl-Shabi M
dc.contributor.departmentMechanical Engineering
dc.date.accessioned2025-02-27T14:24:56Z
dc.date.available2025-02-27T14:24:56Z
dc.date.issued2021-01-01
dc.date.updated2025-02-27T14:24:56Z
dc.description.abstractIn this paper, an adaptive formulation of the sliding innovation filter (SIF) is presented. The SIF is a recently proposed estimation strategy that has demonstrated robustness to modeling errors and uncertainties. It utilizes a switching gain that is a function of the innovation (measurement error) and sliding boundary layer term. In this paper, a time-varying sliding boundary layer is derived based on minimizing the state error covariance. The resulting solution creates an adaptive formulation of the SIF. The adaptive SIF is applied on a linear aerospace system, and is compared with the well-known Kalman filter (KF) and the standard SIF. The results demonstrate the robustness of the new estimation strategy in the presence of modeling uncertainties and system faults.
dc.identifier.doihttps://doi.org/10.1109/lsp.2021.3089918
dc.identifier.issn1070-9908
dc.identifier.issn1558-2361
dc.identifier.urihttp://hdl.handle.net/11375/31120
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subject4006 Communications Engineering
dc.subject4007 Control Engineering, Mechatronics and Robotics
dc.subject40 Engineering
dc.subject4001 Aerospace Engineering
dc.titleAn Adaptive Formulation of the Sliding Innovation Filter
dc.typeArticle

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