This article is concerned with the distributed H_∞ resilient state estimation problem for a class of nonlinear systems with randomly occurring communication delays and missing measurements in sensor networks. A novel sensor model is proposed, in which two Bernoulli distributed white sequences are introduced to describe the random communication delay and missing measurements in a unified framework. Meanwhile, the estimator gain is allowed to fluctuate within a certain range. Based on the developed model, a novel Lyapunov–Krasovskii functional with multiple delay information terms is constructed, then the stochastic analysis technique and the extended integral inequality are used to calculate the functional derivative. Consequently, the existence conditions for the required distributed estimator are established to ensure that the estimation error system is asymptotically mean-square stable and satisfies the prescribed H_∞ performance constraint, and the desired gain of distributed resilient estimator is also solved by linearizing the nonlinear terms. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.

中文翻译：

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具有随机发生通信延迟和缺失测量的非线性系统的分布式弹性状态估计

本文关注分布式H _∞一类非线性系统的弹性状态估计问题，在传感器网络中具有随机发生的通信延迟和丢失的测量值。提出了一种新颖的传感器模型，其中引入了两个伯努利分布的白色序列来描述统一框架中的随机通信延迟和缺失测量。同时，允许估计器增益在一定范围内波动。在该模型的基础上，构造了一个具有多个延迟信息项的新型Lyapunov-Krasovskii泛函，然后利用随机分析技术和扩展积分不等式计算泛函导数。最后，H _∞性能约束，分布式弹性估计器的期望增益也通过线性化非线性项来解决。最后，给出了一个数值例子来说明所提算法的有效性。