Dissipativity of Markovian multiple‐weighted coupled neural networks with dynamic event‐triggered pinning control
Weizhong Chen, Yang Zhang, Yelei Zheng · IET Control Theory and Applications · 2020
In this study, the ‐ ‐dissipativity problem is addressed for Markovian multiple‐weighted coupled neural networks (MWCNNs) with coupling delays by using pinning control and dynamic event‐triggered mechanism. By controlling a small number of nodes in the network combining with dynamic event‐triggered strategy, the system resources can not only be utilised more efficiently but also more conducive to engineering implementation. First, the authors propose a ‐ ‐dissipativity condition of Markovian MWCNNs. Second, pinning controller and dynamic event‐triggered scheme are both designed based on the derived dissipativity criterion. Furthermore, the elimination of Zeno phenomenon is proofed for the proposed event‐triggered method. Finally, a numerical example is provided to verify the admissibility and effectiveness of the acquired results.