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Sampled-Data State Estimation for Complex Networks With Partial Measurements
DOI:10.1109/TSMC.2018.2865097.png)
摘要
En 中文
This paper addresses the sampled-data state estimation problem for complex networks using partial nodes' measurements. A hybrid observer network with partial control is developed to estimate the state information. The key point of the hybrid observer network is that the state observer network is continuous-time by introducing an output predictor. Besides, the hybrid observer only requires a fraction of nodes' sampled measurements with partial control technique. It reduces the state estimation cost and improves the estimation effectiveness. Some criteria are developed to guarantee that the proposed observer network is an exponential observer. Finally, simulation example validates the proposed approach.
Keyword:
Observers
Complex networks
Couplings
Feedback control
Position measurement
Complex networks
partial control
sampled-data observer
state estimation
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期刊
IF:
10.5
论文数:
1.1W
被引数:
5.0W
机构
引用论文
Sampled-data state estimation for complex dynamical networks with time-varying delay and stochastic sampling具有时变时滞和随机采样的复杂动态网络的采样数据状态估计
NEUROCOMPUTING
IF6.5

