Adaptive Event-Triggered Synchronization of Networked Neural Networks with Time-Varying Delay Subject to Actuator Saturation. (7th July 2021)

• Record Type: Journal Article
• Authors: Xu, Yao; Wang, Renren; Lu, Hongqian; Song, Xingxing; Deng, Yahan; Zhou, Wuneng
• Other Names: Dinh Thach Ngoc Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-07-07
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/9957624
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : This paper discusses the adaptive event-triggered synchronization problem of a class of neural networks (NNs) with time-varying delay and actuator saturation. First, in view of the limited communication channel capacity of the network system and unnecessary data transmission in the NCSs, an adaptive event-triggered scheme (AETS) is introduced to reduce the network load and improve network utilization. Second, under the AETS, the synchronization error model of the delayed master-slave synchronization system is constructed with actuator saturation. Third, based on Lyapunov–Krasovskii functional (LKF), a new sufficient criterion to guarantee the asymptotic stability of the synchronization error system is derived. Moreover, by solving the stability criterion expressed in the form of a set of linear matrix inequalities (LMIs), some necessary parameters of the system are obtained. At last, two examples are expressed to demonstrate the feasibility of this method.