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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31286
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dc.contributor.authorGadsden SA-
dc.contributor.authorAl-Shabi M-
dc.date.accessioned2025-03-01T22:57:53Z-
dc.date.available2025-03-01T22:57:53Z-
dc.date.issued2020-01-12-
dc.identifier.urihttp://hdl.handle.net/11375/31286-
dc.description.abstractIn this paper, a study of estimation strategies based on variable structure and sliding mode theory is performed. The smooth variable structure filter (SVSF) and the new sliding innovation filter (SIF) are based on similar sliding mode concepts but with some notable differences. The relevant literature and background are explored and the SVSF and SIF estimation algorithms are presented. For comparison purposes, the two estimation strategies are applied on a mechatronic system. The results indicate that although both the SVSF and SIF provide robust estimates to faults, the SIF formulation provides slightly more accurate estimates while maintaining robustness, and is less computationally complex.-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
dc.subject4901 Applied Mathematics-
dc.subject49 Mathematical Sciences-
dc.subject4007 Control Engineering, Mechatronics and Robotics-
dc.subject40 Engineering-
dc.titleA Study of Variable Structure and Sliding Mode Filters for Robust Estimation of Mechatronic Systems-
dc.typeArticle-
dc.date.updated2025-03-01T22:57:53Z-
dc.contributor.departmentMechanical Engineering-
dc.identifier.doihttps://doi.org/10.1109/iemtronics51293.2020.9216381-
Appears in Collections:Mechanical Engineering Publications

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