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/

Global: Zendy Tools annual

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

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper considers the problem of simultaneous sensor fault detection,isolation, and networked estimation of linear full-rank dynamical systems. Theproposed networked estimation is a variant of single time-scale protocol and isbased on (i) consensus on \textit{a-priori} estimates and (ii) measurementinnovation. The necessary connectivity condition on the sensor network andstabilizing block-diagonal gain matrix is derived based on our previous works.Considering additive faults in the presence of system and measurement noise,the estimation error at sensors is derived and proper residuals are defined forfault detection. Unlike many works in the literature, no simplifyingupper-bound condition on the noise is considered and we assume Gaussiansystem/measurement noise. A probabilistic threshold is then defined for faultdetection based on the estimation error covariance norm. Finally, agraph-theoretic sensor replacement scenario is proposed to recover possibleloss of networked observability due to removing the faulty sensor. We examinethe proposed fault detection and isolation scheme on an illustrative academicexample to verify the results and make a comparison study with relatedliterature.

Sensor Fault Detection and Isolation via Networked Estimation: Full-Rank Dynamical Systems