A heuristic Kalman filter for a class of nonlinear systems

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dc.contributor.author Saab, Samer S.
dc.date.accessioned 2019-07-31T10:09:07Z
dc.date.available 2019-07-31T10:09:07Z
dc.date.copyright 2004 en_US
dc.date.issued 2019-07-31
dc.identifier.issn 0018-9286 en_US
dc.identifier.uri http://hdl.handle.net/10725/11179
dc.description.abstract One of the basic assumptions involved in the "optimality" of the Kalman filter theory is that the system under consideration must be linear. If the model is nonlinear, a linearization procedure is usually performed in deriving the filtering equations. This approach requires the nonlinear system dynamics to be differentiable. This note is an attempt to develop a heuristic Kalman filter for a class of nonlinear systems, with bounded first-order growth, that does not require the system dynamics to be differentiable. The proposed filter approximates the nonlinear state function by its state argument multiplied by a particular gain matrix only in the recursion of the estimation error covariance matrix. Under certain conditions, the error covariance remains bounded by bounds which can be precomputed from noise and system models, and the upper bound tends to zero when the state noise covariance tends to zero. A numerical example, with backlash nonlinearity, is also added. en_US
dc.language.iso en en_US
dc.title A heuristic Kalman filter for a class of nonlinear systems en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SOE en_US
dc.author.idnumber 199690250 en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal IEEE Transactions on Automatic Control en_US
dc.journal.volume 49 en_US
dc.journal.issue 12 en_US
dc.article.pages 2261-2265 en_US
dc.keywords Hystereis en_US
dc.keywords Kalman filtering en_US
dc.keywords Nonlinear systems en_US
dc.identifier.doi http://dx.doi.org/10.1109/TAC.2004.838485 en_US
dc.identifier.ctation Saab, S. S. (2004). A heuristic Kalman filter for a class of nonlinear systems. IEEE transactions on automatic control, 49(12), 2261-2265. en_US
dc.author.email ssaab@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/1369403 en_US
dc.orcid.id https://orcid.org/0000-0003-0124-8457 en_US
dc.author.affiliation Lebanese American University en_US

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