Partial-nodes-based state estimation for complex networks with unbounded distributed delays

Yurong Liu, Zidong Wang, Yuan Yuan, Fuad E. Alsaadi

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81 引用 (Scopus)

摘要

In this brief, the new problem of partial-nodes-based (PNB) state estimation problem is investigated for a class of complex network with unbounded distributed delays and energy-bounded measurement noises. The main novelty lies in that the states of the complex network are estimated through measurement outputs of a fraction of the network nodes. Such fraction of the nodes is determined by either the practical availability or the computational necessity. The PNB state estimator is designed such that the error dynamics of the network state estimation is exponentially ultimately bounded in the presence of measurement errors. Sufficient conditions are established to ensure the existence of the PNB state estimators and then the explicit expression of the gain matrices of such estimators is characterized. When the network measurements are free of noises, the main results specialize to the case of exponential stability for error dynamics. Numerical examples are presented to verify the theoretical results.

源语言英语
页(从-至)3906-3912
页数7
期刊IEEE Transactions on Neural Networks and Learning Systems
29
8
DOI
出版状态已出版 - 8月 2018
已对外发布

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