Tracking control of T-S fuzzy systems under probabilistic constraints and fading channels

Hongjian Liu, Jingfei Zhang and Zhina Zhang

International Journal of Systems Science, 2025, vol. 56, issue 1, 88-97

Abstract: This work investigates the probabilistic-constrained tracking control problem for T-S fuzzy systems under fading channels described by the memoryless multiplicative noise model. The main control objective is to confine the tracking error into its pre-given bounds no lower than a certain probability. To this end, a tracking controller is firstly synthesised by introducing the fading parameter as an amplification factor towards ‘retrieving’ the original information to some extent. An auxiliary function and the multi-dimensional Chebyshev inequality make it possible to derive sufficient conditions such that the tracking error falls into its specified domain with a frequency larger than a pre-given value. By employing an inequality involving unmatched membership functions of the controller and fuzzy system, the favourite property of matched membership functions can be employed. A numerical example illustrates the effectiveness of the proposed method.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2024.2388325 (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:56:y:2025:i:1:p:88-97

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2024.2388325

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 ().