Decentralized event-triggered H∞ control for neural networks subject to cyber-attacks

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.