Aperiodic Optimal Linear Estimation for Networked Systems With Communication Uncertainties
Aperiodic Optimal Linear Estimation for Networked Systems With Communication Uncertainties
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DOI：
10.1109/tcyb.2017.2684136
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发表时间：
2017-04
影响因子：
11.8
通讯作者：
Wen-an Zhang;Michael Z. Q. Chen;Andong Liu;Steven Liu
中科院分区：
文献类型：
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作者：
Wen-an Zhang;Michael Z. Q. Chen;Andong Liu;Steven Liu
研究了具有通信不确定性（包括时延和数据丢失）的网络化系统的非周期最优线性估计器设计问题，其中采样和估计是非均匀和异步的。基于量测融合的思想，提出了两种设计非周期估计器的方法，并证明了该估计器与量测增广法设计的估计器在性能上是等价的。此外，通过使用新提出的测量重传方案，与常用的保持输入和零输入方案相比，估计性能得到改善，通过该方案，丢失的测量一旦丢失就不再使用。
The aperiodic optimal linear estimator design problem is investigated in this paper for networked systems with communication uncertainties, including delays and data losses, where the sampling and estimation are nonuniform and asynchronous. Based on the idea of measurement fusion, two approaches are proposed to design the aperiodic estimators, and it is shown that the estimator is equivalent to that designed by the measurement augmentation method in performance. Moreover, the estimation performance is improved by using a newly proposed measurement retransmission scheme as compared with the commonly used hold-input and zero-input schemes, by which the lost measurements are never used once they are lost.