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dc.contributor.authorWang, D-
dc.contributor.authorWang, Z-
dc.contributor.authorLi, G-
dc.contributor.authorWang, W-
dc.identifier.citationIEEE Sensors Journal, 16(12), pp. 4940 - 4948, (2016)en_US
dc.description.abstractIn this paper, the distributed filtering problem is investigated for a class of switched nonlinear positive systems over sensor networks. The randomly varying nonlinearities and missing measurements, which are governed by two mutually independent Bernoulli distributed white sequences, are taken into account. Based on the output measurements of the individual sensor and its neighbors, the distributed filter with positivity constraint is designed to ensure the prescribed average l∞ performance index of the estimation error dynamics. Special attention is paid to preserve the positivity of the underlying system as well as the sparseness of the addressed network topology. Sufficient conditions are established on the existence of the desired filters by using the linear programming approach, and the filter gains are subsequently characterized. A simulation example is provided to illustrate the effectiveness of the proposed filtering method.en_US
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China under Grant 61104114, Grant 61201035, Grant 61374070, and Grant 61473055 and in part by the Liaoning Province Science Foundation under Grant 2015020075 and in part by the General Projects for Science Research in the Liaoning Province under Grant L2014026.en_US
dc.format.extent4940 - 4948-
dc.subjectDistributed filteringen_US
dc.subjectMissing measurementsen_US
dc.subjectPositive systemsen_US
dc.subjectStochastic nonlinearityen_US
dc.subjectSwitched systemsen_US
dc.titleDistributed filtering for switched nonlinear positive systems with missing measurements over sensor networksen_US
dc.relation.isPartOfIEEE Sensors Journal-
Appears in Collections:Dept of Computer Science Research Papers

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