In this paper, distributed security filtering is investigated for networked switched systems under the round-robin protocol (RRP). In order to fully take the practical situation into account, a cyber attack without additional bounded constraint is considered by introducing the neural network approximate technique. Moreover, the scattered sensor nodes are universally utilized to transmit and collect system information. The distributed filtering is proposed for the networked switched systems to estimate the system output. In order to ease data collisions, RRP is taken to schedule signal communication through the shared network. By constructing a token-dependent and mode-dependent Lyapunov function, sufficient conditions are given to ensure the filtering error system under cyber attack is finite-time bounded. The filtering gains are determined by solving a set of linear matrix inequalities. Finally, the availability of the acquired methods is verified by a PWM-driven boost converter model.

中文翻译：

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网络交换系统的基于神经网络的分布式安全过滤

本文研究了循环协议（RRP）下网络交换系统的分布式安全过滤。为充分考虑实际情况，通过引入神经网络近似技术，考虑无附加有界约束的网络攻击。此外，分散的传感器节点普遍用于传输和收集系统信息。针对网络化交换系统提出了分布式滤波来估计系统输出。为了缓解数据冲突，采用 RRP 来调度通过共享网络的信号通信。通过构造一个token-dependent和mode-dependent Lyapunov函数，给出了保证网络攻击下的过滤误差系统是有限时间有界的充分条件。通过求解一组线性矩阵不等式来确定滤波增益。最后，通过 PWM 驱动的升压转换器模型验证了所获得方法的可用性。