Event-triggered-based fault detection filter design for discrete-time networked singular systems
Kezhen He,
Qiyi Xu,
Kangxin Sun and
Baichao Song
International Journal of Systems Science, 2026, vol. 57, issue 2, 401-413
Abstract:
This paper studies the issue of event-triggered fault detection filtering for a category of discrete-time networked singular systems (DNSSs). The output signal from the plant to the fault detection filter (FDF) is assumed to be transmitted through the network channel. This study is dedicated to the design of an FDF that ensures the residual system is admissible and fulfils some expected $ {H}_\infty $ H∞ performances. To diminish the volume of data transmitted over the limited bandwidth communication channel, an event-triggered scheme (ETS) is introduced. A networked FDF is constructed considering the network-induced delays, and a singular time-delay residual augmented system (STDRAS) is derived. By employing Lyapunov stability theory, several new criteria are established as linear matrix inequalities (LMIs), ensuring the admissibility of STDRAS and satisfying the expected $ {H}_\infty $ H∞ performance. Sufficient conditions are obtained for the existence of FDF and ETS. Finally, two examples are given to showcase the effectiveness of the proposed method.
Date: 2026
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2025.2504054 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:57:y:2026:i:2:p:401-413
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2025.2504054
Access Statistics for this article
International Journal of Systems Science is currently edited by Visakan Kadirkamanathan
More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().