Fuzzy adaptive finite-time consensus tracking control for nonlinear multi-agent systems

Lili Zhang, Bing Chen, Chong Lin and Yun Shang

International Journal of Systems Science, 2021, vol. 52, issue 7, 1346-1358

Abstract: This paper focuses on the finite-time consensus tracking control problem of nonlinear multi-agent systems. Dynamics of each agent has completely unknown nonlinear terms that cannot be directly used for control design. Therefore, fuzzy logic systems are employed to approximate these nonlinear functions. Furthermore, a finite-time fuzzy adaptive consensus tracking protocol is proposed for a class of nonlinear multi-agent systems by using integral-type Lyapunov functions. The developed adaptive backstepping design scheme successfully avoids the singularity problem of the derivatives of virtual control signals. It is shown that with the presented control protocol, the consensus tracking errors converge to a small neighbourhood of the origin in finite time, and the other signals of multi-agent systems are bounded. Finally, a numerical example is used to verify the effectiveness of the proposed control protocol.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2020.1856450 (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:52:y:2021:i:7:p:1346-1358

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

DOI: 10.1080/00207721.2020.1856450

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 ().