Partial-Nodes-Based State Estimation for Complex Networks With Unbounded Distributed Delays

被引:79
|
作者
Liu, Yurong [1 ,2 ]
Wang, Zidong [3 ]
Yuan, Yuan [3 ,4 ]
Alsaadi, Fuad E. [2 ]
机构
[1] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China
[2] King Abdulaziz Univ, Fac Engn, Jeddah 21589, Saudi Arabia
[3] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, Middx, England
[4] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Complex network; exponentially ultimately boundedness; fraction of the nodes; state estimation; unbounded distributed time-delay; COUPLED NEURAL-NETWORKS; PINNING SYNCHRONIZATION; DYNAMICAL NETWORKS; TIME-DELAY; SYSTEMS; DISCRETE; INFORMATION; COUPLINGS;
D O I
10.1109/TNNLS.2017.2740400
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码:3906 / 3912
页数:7
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