Event-Triggered $$H_{\infty }$$ Filtering for A Class of Nonlinear Systems Under DoS Attacks

Abstract

This paper investigates event-triggered \(H_{\infty }\) filtering for a class of discrete-time nonlinear systems subject to denial-of-service (DoS) attacks. Since the communication network in the networked systems is vulnerable to malicious cyber-attacks, this paper models DoS attacks as a Bernoulli random variable, which results in stochastic filtering error system. Besides, we use adaptive event-triggered communication to ensure that the least amount of information is transmitted over the network. For the filtering error system under the effect of event-triggered communication and DoS attacks, we provide sufficient conditions on guaranteeing the stability and prescribed \(H_{\infty }\) performance, where the \(H_{\infty }\) filter and event-triggered parameters are co-designed using the linear matrix inequality approach. Finally, two illustrative examples are provided to demonstrate the effectiveness of the proposed method.