Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays
Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays
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DOI：
10.1145/2379799.2379803
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发表时间：
2012-11
期刊：
影响因子：
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通讯作者：
Jinling Liang;Zidong Wang;Bo Shen;Xiaohui Liu
中科院分区：
文献类型：
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作者：
Jinling Liang;Zidong Wang;Bo Shen;Xiaohui Liu
本文研究了传感器网络中一类动态系统的分布式状态估计问题。目标对象用一组微分方程来描述，微分方程受布朗运动和随机非线性（ron）的扰动。本文研究的是网络诱导的随机延迟态对当前延迟态的调节。通过传感器传输的可用测量输出，设计了分布式状态估计器来估计目标系统的状态，其中每个传感器可以根据给定的拓扑结构以有向图的方式与相邻传感器通信。该方法采用分布式方式进行状态估计，适合在线应用。利用Lyapunov泛函结合随机分析技术，建立了几个与时滞相关的准则，不仅保证了估计误差在均方全局渐近稳定，而且保证了期望估计量增益的存在性，当求解某些矩阵不等式时，期望估计量增益可以显式表示。最后给出了一个数值算例，验证了所设计的分布式状态估计器。
This article is concerned with a new distributed state estimation problem for a class of dynamical systems in sensor networks. The target plant is described by a set of differential equations disturbed by a Brownian motion and randomly occurring nonlinearities (RONs) subject to time delays. The RONs are investigated here to reflect network-induced randomly occurring regulation of the delayed states on the current ones. Through available measurement output transmitted from the sensors, a distributed state estimator is designed to estimate the states of the target system, where each sensor can communicate with the neighboring sensors according to the given topology by means of a directed graph. The state estimation is carried out in a distributed way and is therefore applicable to online application. By resorting to the Lyapunov functional combined with stochastic analysis techniques, several delay-dependent criteria are established that not only ensure the estimation error to be globally asymptotically stable in the mean square, but also guarantee the existence of the desired estimator gains that can then be explicitly expressed when certain matrix inequalities are solved. A numerical example is given to verify the designed distributed state estimators.