Iterative learning consensus control for switched discrete-time multi-agent systems based on the 2-D linear discrete model

Song Yang and Xiao-Dong Li

International Journal of Systems Science, 2025, vol. 56, issue 10, 2231-2245

Abstract: In this article, a class of switched nonlinear discrete-time heterogeneous (NDTH) multi-agent systems (MASs) with switching signals in both agent dynamics and communication topologies are considered, and a distributed iterative learning control (ILC) law is proposed for the output consensus of the switched NDTH MAS so that the outputs of all follower agents can well track the leader agent. With the proposed ILC controller, the iterative learning dynamic process of the switched NDTH MAS is firstly formulated as a two-dimensional (2-D) linear discrete Roesser model with specified boundary states at each switching sub-interval. Afterwards, according to the exploited properties on solution of the 2-D linear discrete Roesser model, a sufficient convergence theorem for the presented ILC controller is derived. At last, the validity of the ILC-based consensus controller is illustrated through a simulation experiment.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2024.2441456 (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:10:p:2231-2245

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

DOI: 10.1080/00207721.2024.2441456

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 ().