Shen Bo, Wang Zidong, Wang Dong, Liu Hongjian
IEEE Trans Cybern. 2020 Aug;50(8):3605-3615. doi: 10.1109/TCYB.2019.2932460. Epub 2019 Aug 23.
This article is concerned with the distributed recursive filtering issue for stochastic discrete time-varying systems subjected to both state saturations and round-robin (RR) protocols over sensor networks. The phenomenon of state saturation is considered to better describe practical engineering. The RR protocol is introduced to mitigate a network burden by determining which component of the sensor node has access to the network at each transmission instant. The purpose of the issue under consideration is to construct a distributed recursive filter such that a certain filtering error covariance's upper bound can be found and the corresponding filter parameters' explicit expression is given with both state saturations and RR protocols. By taking advantage of matrix difference equations, a filtering error covariance's upper bound can be presented and then be minimized by appropriately designing filter parameters. In particular, by using a matrix simplification technique, the sensor network topology's sparseness issue can be tackled. Finally, the feasibility for the addressed filtering scheme is demonstrated by an example.
本文关注的是传感器网络中受状态饱和和循环（RR）协议影响的随机离散时变系统的分布式递归滤波问题。考虑状态饱和现象是为了更好地描述实际工程。引入RR协议是为了通过确定传感器节点的哪个组件在每个传输时刻可以访问网络来减轻网络负担。所考虑问题的目的是构建一个分布式递归滤波器，以便能够找到某个滤波误差协方差的上界，并给出相应滤波器参数的显式表达式，同时考虑状态饱和和RR协议。通过利用矩阵差分方程，可以给出滤波误差协方差的上界，然后通过适当地设计滤波器参数将其最小化。特别地，通过使用矩阵简化技术，可以解决传感器网络拓扑的稀疏性问题。最后，通过一个例子证明了所提出的滤波方案的可行性。
