English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The paper considers a distributed robust estimation problem over a networkwith Markovian randomly varying topology. The objective is to deal with networkvariations locally, by switching observer gains at affected nodes only. Wepropose sufficient conditions which guarantee a suboptimal $H_\infty$ level ofrelative disagreement of estimates in such observer networks. When the statusof the network is known globally, these sufficient conditions enable thenetwork gains to be computed by solving certain LMIs. When the nodes are torely on a locally available information about the network topology, additionalrank constraints are used to condition the gains, given this information. Theresults are complemented by necessary conditions which relate properties of theinterconnection graph Laplacian to the mean-square detectability of the plantthrough measurement and interconnection channels.

Distributed robust estimation over randomly switching networks using $H_\infty$ consensus