Event-Triggered Output-Feedback Control for Synchronization of Delayed Neural Networks

Autor: Zhang, Liruo, Zhang, Duo, Nguang, Sing Kiong, Swain, Akshya Kumar, Yu, Zhongjing
Zdroj: IEEE Transactions on Cybernetics; September 2023, Vol. 53 Issue: 9 p5618-5630, 13p
Abstrakt: This article proposes a novel discrete event-triggered scheme (DETS) for the synchronization of delayed neural networks (NNs) using the dynamic output-feedback controller (DOFC). The proposed DETS uses both the current and past samples to determine the next trigger, unlike the traditional event-triggered scheme (ETS) that uses only the current sample. The proposed DETS is employed in a dual setup for two network channels to significantly reduce redundant data transmission. A DOFC is designed to achieve the synchronization of the NNs. Stability criteria of the synchronisation error system are derived based on the Lyapunov–Krasovskii functional method, and the co-design of the DOFC and DETS parameters are accomplished using the Cone-complementarity linearization (CCL) approach. The effectiveness and advantages of the proposed method are illustrated considering an example of the chaotic system.
Databáze: Supplemental Index