Discontinuous event-trigger scheme for global stabilization of state-dependent switching neural networks with communication delay
Yingjie Fan(樊英杰)1, Zhen Wang(王震)2,†, Jianwei Xia(夏建伟)3, and Hao Shen(沈浩)4
1 College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China; 2 College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China; 3 School of Mathematical Science, Liaocheng University, Liaocheng 252059, China; 4 College of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan 243032, China
Abstract This paper is concerned with the global stabilization of state-dependent switching neural networks (SDSNNs) via discontinuous event-triggered control with network-induced communication delay. Aiming at decreasing triggering times, a discontinuous event-trigger scheme is utilized to determine whether the sampling information is required to be sent out or not. Meanwhile, under the effect of communication delay, the trigger condition and SDSNNs are transformed into two tractable models by designing a fictitious delay function. Then, using the Lyapunov-Krasovskii stability theory, some inequality estimation techniques, and extended reciprocally convex combination method, two sufficient criteria are established for ensuring the global stabilization of the resulting closed-loop SDSNNs, respectively. A unified framework is derived that has the ability to handle the simultaneous existence of the communication delay, the properties of discontinuous event-trigger scheme, as well as feedback controller design. Additionally, the developed results demonstrate a quantitative relationship among the event trigger parameter, communication delay, and triggering times. Finally, two numerical examples are presented to illustrate the usefulness of the developed stabilization scheme.
Yingjie Fan(樊英杰), Zhen Wang(王震), Jianwei Xia(夏建伟), and Hao Shen(沈浩) Discontinuous event-trigger scheme for global stabilization of state-dependent switching neural networks with communication delay 2021 Chin. Phys. B 30 030202
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