This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.

中文翻译：

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传感器网络上一般非线性系统事件触发过滤的集隶属方法


本文研究传感器网络事件触发通信协议下一类一般离散时间非线性系统的分布式集合成员过滤问题。为了减轻通信负担，每个智能传感节点仅在满足预定的基于事件的媒体访问条件时才向相邻节点广播其测量结果。根据区间数学理论，设计了一种递归分布式集隶属方案，通过充分融合相邻节点的测量值来获得包含感兴趣目标状态的椭球集，其中拉格朗日余数的准确估计和基于事件的媒体-巧妙地利用访问条件来提高过滤器性能。此外，这种方案仅依赖于邻居信息和本地邻接权重，从而满足传感器网络的可扩展性要求。此外，还开发了一种优化算法来最小化估计椭球集的轨迹，并且还深入讨论了所采用的事件触发阈值的影响。最后，利用仿真示例来说明所提出的分布式集合成员过滤方案的有用性。