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

dc.contributor.author	Gadsden SA
dc.contributor.author	Afshari HH
dc.contributor.department	Mechanical Engineering
dc.date.accessioned	2025-02-27T20:15:41Z
dc.date.available	2025-02-27T20:15:41Z
dc.date.issued	2015-11-13
dc.date.updated	2025-02-27T20:15:41Z
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.identifier.doi	https://doi.org/10.1115/imece2015-50966
dc.identifier.isbn	978-0-7918-5739-7
dc.identifier.uri	http://hdl.handle.net/11375/31229
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

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