In this article, the ${\mathcal{H}}_{\infty }$ filtering issue is considered for discrete-time nonlinear networked systems subject to event-triggered communication scheme, dynamic quantization, and stochastic cyber attacks. The considered nonlinear networked system is described by the Takagi–Sugeno (T–S) fuzzy model. The event-triggered policy and the dynamic quantizer will be considered to realize the effective use of the restricted network bandwidth resources. Moreover, a stochastic variable that satisfies the Bernoulli random binary distribution is employed to characterize the effects of stochastic cyber attacks. This paper focus on the design of full- and reduced-order event-triggered ${\mathcal{H}}_{\infty }$ filters and the dynamic parameter of the quantizer such that the filtering error system is stochastically stable and satisfies a predefined ${\mathcal{H}}_{\infty }$ filtering performance. The sufficient design conditions for the event-triggered ${\mathcal{H}}_{\infty }$ filters and the dynamic parameter of the quantizer are proposed based on linear matrix inequalities (LMIs). Finally, an example based on practical application will be used to verify the effectiveness of the presented design methods.

在这篇文章中，${\mathcal{H}}_{\infty }$考虑事件触发通信方案、动态量化和随机网络攻击的离散时间非线性网络系统的滤波问题。所考虑的非线性网络系统由 Takagi-Sugeno (T-S) 模糊模型描述。将考虑事件触发策略和动态量化器来实现受限网络带宽资源的有效利用。此外，使用满足伯努利随机二进制分布的随机变量来表征随机网络攻击的影响。本文重点介绍全阶和降阶事件触发的设计${\mathcal{H}}_{\infty }$滤波器和量化器的动态参数，使得滤波误差系统是随机稳定的并满足预定义的${\mathcal{H}}_{\infty }$过滤性能。事件触发的充分设计条件${\mathcal{H}}_{\infty }$基于线性矩阵不等式（LMI）提出了滤波器和量化器的动态参数。最后通过一个基于实际应用的实例来验证所提出的设计方法的有效性。