Fault detection filter design for interval type-2 fuzzy systems under a novel adaptive event-triggering mechanism
Xuhuan Xie,
Shanbin Li and
Bugong Xu
International Journal of Systems Science, 2019, vol. 50, issue 13, 2510-2528
Abstract:
This study is concerned with the problem of event-based fault detection (FD) filter design for interval type-2 fuzzy systems in a network environment. Firstly, by employing the properties of exponential function, a novel adaptive event-triggering mechanism (AETM) where the boundedness of threshold function is guaranteed and the size of threshold function is inversely proportional to the size of 2-norm of the sampled-output-error is proposed to dynamically adapt the variation of the system and to reduce the unnecessary information communication between the sensor and the filter. Secondly, in the framework of time-delay systems, the FD system with a networked filter and an AETM is modelled as an interval time-varying delayed system. Then, a sufficient condition to implement co-design of the parameters of filter and trigger is obtained by applying a simple Lyapunov–Krasovskii functionals, combined with recently developed Wirtinger-based integral inequality and reciprocally convex inequality, and utilising congruent transformation method. Thirdly, based on the obtained co-design condition, an optimisation algorithm subject to convex constraints for the tradeoffs between resource utilisation and $H_\infty $H∞ performance of the FD system is further developed. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed scheme.
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2019.1671531 (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:50:y:2019:i:13:p:2510-2528
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2019.1671531
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 ().