Event-triggered adaptive control for delayed memristive neural networks with unknown parameters and external disturbances

Zhenning Zhang, Xiaowu Mu and Zenghui Hu

International Journal of Systems Science, 2023, vol. 54, issue 9, 2021-2039

Abstract: The synchronisation problem is studied for master–slave memristive neural networks (MNNs) in this paper. For alleviating the burden of communication bandwidth, a novel event-triggered scheme of data transmission is designed in the sensor-to-controller (S-C) channel. To deal with the unknown parameters and disturbances of master–slave MNNs, the adaptive controller is designed with the system states of triggering instants. Different from existing results about event-triggered adaptive control (ETAC) for MNNs, in which the event-triggered mechanism (ETM) is installed in the controller-to-actuator (C-A) channel, the event-triggered scheme in this paper is designed between the sensor and the controller, so the information flow of S-C channel is discontinuous. The adaptive laws can only use discrete-time system states transmitted at triggering instants to update control gains in this paper. By means of the Lyapunov methods, adaptive control theories and event-triggered techniques, sufficient conditions for synchronisation and quasi-synchronisation are obtained. At the same time, the designed ETM can avoid Zeno behaviour theoretically. Finally, the validity of the obtained results is shown by two simulation examples.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2023.2212675 (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:54:y:2023:i:9:p:2021-2039

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

DOI: 10.1080/00207721.2023.2212675

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 ().