Event-triggered communication for passivity and synchronisation of multi-weighted coupled neural networks with and without parameter uncertainties
Wang, Yihao and Huang, Yanli and Yang, Erfu (2020) Event-triggered communication for passivity and synchronisation of multi-weighted coupled neural networks with and without parameter uncertainties. IET Control Theory and Applications, 14 (9). pp. 1228-1239. ISSN 1751-8644
|
Text (Wang-etal-IET-CTA-2020-Event-triggered-communication-for-passivity-and-synchronization)
Wang_etal_IET_CTA_2020_Event_triggered_communication_for_passivity_and_synchronization.pdf Accepted Author Manuscript Download (1MB)| Preview |
Abstract
A multi-weighted coupled neural networks (MWCNNs) model with event-triggered communication is studied here. On the one hand, the passivity of the presented network model is studied by utilising Lyapunov stability theory and some inequality techniques, and a synchronisation criterion based on the obtained output-strict passivity condition of MWCNNs with eventtriggered communication is derived. On the other hand, some robust passivity and robust synchronisation criteria based on output-strict passivity of the proposed network with uncertain parameters are presented. At last, two numerical examples are provided to testify the effectiveness of the output-strict passivity and robust synchronisation results.
Creators(s): |
Wang, Yihao, Huang, Yanli and Yang, Erfu ![]() | Item type: | Article |
---|---|
ID code: | 72067 |
Keywords: | multi-weighted coupled neural networks, event-triggered communication, passivity, Electrical engineering. Electronics Nuclear engineering, Control and Optimization, Control and Systems Engineering, Computer Science Applications, Electrical and Electronic Engineering, Human-Computer Interaction |
Subjects: | Technology > Electrical engineering. Electronics Nuclear engineering |
Department: | Faculty of Engineering > Design, Manufacture and Engineering Management |
Depositing user: | Pure Administrator |
Date deposited: | 16 Apr 2020 12:56 |
Last modified: | 12 Feb 2021 04:42 |
URI: | https://strathprints.strath.ac.uk/id/eprint/72067 |
Export data: |