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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31200
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dc.contributor.authorGadsden SA-
dc.contributor.authorMcCullough K-
dc.contributor.authorHabibi SR-
dc.date.accessioned2025-02-27T19:33:37Z-
dc.date.available2025-02-27T19:33:37Z-
dc.date.issued2011-06-01-
dc.identifier.issn0743-1619-
dc.identifier.issn2378-5861-
dc.identifier.urihttp://hdl.handle.net/11375/31200-
dc.description.abstractIn this paper, a new type of interacting multiple model (IMM) is introduced for the purposes of fault detection and diagnosis. The standard IMM is combined with a relatively new filtering method referred to as the smooth variable structure filter (SVSF). The SVSF is a type of sliding mode estimator, formulated in a predictor-correct fashion. It keeps the estimated state close to the true trajectory, and creates a stable estimation process. The combined method, referred to as the SVSF-IMM, is applied to an electrohydrostatic actuator (EHA). The results of the experiment are compared with the common form of the IMM, which utilizes the popular Kalman filter (KF). © 2011 AACC American Automatic Control Council.-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
dc.subject4007 Control Engineering, Mechatronics and Robotics-
dc.subject40 Engineering-
dc.subject4001 Aerospace Engineering-
dc.titleFault detection and diagnosis of an electrohydrostatic actuator using a novel interacting multiple model approach-
dc.typeArticle-
dc.date.updated2025-02-27T19:33:37Z-
dc.contributor.departmentMechanical Engineering-
dc.identifier.doihttps://doi.org/10.1109/acc.2011.5991440-
Appears in Collections:Mechanical Engineering Publications

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