Indexed on: 01 Jun '18Published on: 30 May '18Published in: Information Sciences
Publication date: August 2018 Source:Information Sciences, Volumes 457–458 Author(s): Lijuan Zha, Engang Tian, Xiangpeng Xie, Zhou Gu, Jie Cao This paper addresses the problem of decentralized event-triggered H ∞ control for neural networks subject to limited network-bandwidth and cyber-attacks. In order to alleviate the network transmission burden, a decentralized event-triggered scheme is employed to determine whether the sensor measurements should be sent out or not. Each sensor can decide the transmitted sensor measurements locally according to the corresponding event-triggered condition. It is assumed that the network transmissions may be modified by the occurrence of the random cyber-attacks. A Bernoulli distributed variable is employed to reflect the success ration of the launched cyber-attacks. The Lyapunov method is employed to derive a sufficient condition such that the closed-loop system is asymptotically stable and achieves the prescribed H ∞ level. Moreover, the desired H ∞ controller gains are derived provided that the sufficient condition is satisfied. Finally, illustrative examples are utilized to show the usefulness of the obtained results.