Open AccessFault detection filtering for continuous-time singular systems under a dynamic event-triggered mechanism
Author(s) -
Qian Zhang,
Huaicheng Yan,
Jun Cheng,
Xisheng Zhan,
Kaibo Shi
Publication year - 2022
Publication title -
discrete and continuous dynamical systems. series s
Language(s) - English
Resource type - Journals
eISSN - 1937-1632
pISSN - 1937-1179
DOI - 10.3934/dcdss.2022023
Subject(s) - transmission (telecommunications) , residual , computer science , event (particle physics) , filter (signal processing) , fault detection and isolation , control theory (sociology) , algorithm , mechanism (biology) , signal (programming language) , fault (geology) , mathematics , real time computing , artificial intelligence , telecommunications , physics , control (management) , quantum mechanics , actuator , computer vision , programming language , seismology , geology
This paper focuses on the problem of fault detection filtering (FDF) for continuous-time singular systems via a dynamic event-triggered mechanism. Firstly, in order to reduce signal transmission and save network resources, a dynamic event-triggered mechanism is adopted. Compared with the static mechanism, the proposed method is more effective on reducing network transmission pressure since a dynamic variable is introduced. Secondly, a novel criterion is derived to guarantee the admissibility of the residual system with a certain \begin{document}$ \mathcal{H}_\infty $\end{document} performance. According to the derived conditions, a new method is given to codesign the desired filter and the event-triggered parameters. Finally, an example is employed to illustrate the validity of the proposed approach.