Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23479
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dc.contributor.authorHuang, C-
dc.contributor.authorShen, B-
dc.contributor.authorZou, L-
dc.contributor.authorShen, Y-
dc.date.accessioned2021-11-09T16:47:59Z-
dc.date.available2021-11-09T16:47:59Z-
dc.date.issued2021-02-10-
dc.identifier.citationHuang, C., Shen, B., Zou, L. and Shen, Y. (2021) ‘Event-Triggering State and Fault Estimation for a Class of Nonlinear Systems Subject to Sensor Saturations’, Sensors (Switzerland), 21 (4), 1242, pp. 1 - 17. doi: 10.3390/s21041242.en_US
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/23479-
dc.description.abstractCopyright: © 2021 by the authors. This paper is concerned with the state and fault estimation issue for nonlinear systems with sensor saturations and fault signals. For the sake of avoiding the communication burden, an event-triggering protocol is utilized to govern the transmission frequency of the measurements from the sensor to its corresponding recursive estimator. Under the event-triggering mechanism (ETM), the current transmission is released only when the relative error of measurements is bigger than a prescribed threshold. The objective of this paper is to design an event-triggering recursive state and fault estimator such that the estimation error covariances for the state and fault are both guaranteed with upper bounds and subsequently derive the gain matrices minimizing such upper bounds, relying on the solutions to a set of difference equations. Finally, two experimental examples are given to validate the effectiveness of the designed algorithm.en_US
dc.format.extent1 - 17-
dc.format.extent1 - 17-
dc.format.mediumElectronic-
dc.language.isoen_USen_US
dc.publisherMDPI AGen_US
dc.rightsCopyright: © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectevent-triggering mechanism (ETM)en_US
dc.subjectnonlinear systemen_US
dc.subjectrecursive estimatoren_US
dc.subjectsensor saturationsen_US
dc.subjectstate and fault estimationen_US
dc.titleEvent-triggering state and fault estimation for a class of nonlinear systems subject to sensor saturationsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.3390/s21041242-
dc.relation.isPartOfSensors (Switzerland)-
pubs.issue4-
pubs.publication-statusPublished-
pubs.volume21-
dc.identifier.eissn1424-8220-
Appears in Collections:Dept of Computer Science Research Papers

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