Optimal linear estimators for systems with multiple random measurement delays and packet dropouts

被引：0

作者：

Yu Luyang ^{[1
]}

Ma Jing ^{[1
]}

Sun Shuli

机构：

[1] Heilongjiang Univ, Sch Math Sci, Harbin 150080, Peoples R China

来源：

26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年

关键词：

Random delay; Packet dropout; Optimal linear estimator; Linear minimum variance; SENSOR DELAY; STATE ESTIMATION; TIME-SYSTEMS; CONSTRAINTS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For linear discrete-time stochastic systems with multiple random measurement delays and packet dropouts, we give a new augmented method by introducing measurement outputs into the augmented state vector. Based on this augmented state vector, the optimal linear estimators including filter, predictor and smoother are developed in the linear minimum variance sense. They can reduce the computational burden compared with the augmented method in the existing literature. A simulation example verifies their effectiveness.

引用

页码：4972 / 4976

页数：5

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