A Review of Smooth Variable Structure Filters: Recent Advances in Theory and Applications

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31229

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DC Field	Value	Language
dc.contributor.author	Gadsden SA	-
dc.contributor.author	Afshari HH	-
dc.date.accessioned	2025-02-27T20:15:41Z	-
dc.date.available	2025-02-27T20:15:41Z	-
dc.date.issued	2015-11-13	-
dc.identifier.isbn	978-0-7918-5739-7	-
dc.identifier.uri	http://hdl.handle.net/11375/31229	-
dc.description.abstract	The smooth variable structure filter (SVSF) is a relatively new state and parameter estimation technique. Introduced in 2007, it is based on the sliding mode concept, and is formulated in a predictor-corrector fashion. The main advantages of the SVSF, over other estimation methods, are robustness to modeling errors and uncertainties, and its ability to detect system changes. Recent developments have looked at improving the SVSF from its original form. This review paper provides an overview of the SVSF, and summarizes the main advances in its theory.	-
dc.publisher	ASME International	-
dc.subject	4901 Applied Mathematics	-
dc.subject	40 Engineering	-
dc.subject	49 Mathematical Sciences	-
dc.title	A Review of Smooth Variable Structure Filters: Recent Advances in Theory and Applications	-
dc.type	Article	-
dc.date.updated	2025-02-27T20:15:41Z	-
dc.contributor.department	Mechanical Engineering	-
dc.identifier.doi	https://doi.org/10.1115/imece2015-50966	-
Appears in Collections:	Mechanical Engineering Publications

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