Optimal minimal-order least-squares estimators via the general two-stage Kalman filter

被引：8

作者：

Hsieh, CS ^{[1
]}

Chen, FC

机构：

[1] Ta Hwa Inst Technol, Dept Elect Engn, Hsinchu 307, Taiwan

[2] Natl Chiao Tung Univ, Dept Elect & Control Engn, Hsinchu 300, Taiwan

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2001年 / 46卷 / 11期

关键词：

least-squares estimator; minimal-order estimator; reduced-order estimator; two-stage Kalman filter;

D O I：

10.1109/9.964689

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A direct derivation of the optimal minimal-order least-squares estimator (OMOLSE) is presented using the recently developed general two-stage Kalman filter (GTSKF). Using this new result, the reduced-order estimators of O'Reilly and Fairman are readily shown to be equivalent. A practical implementation issue to consider these two estimators is also addressed.

引用

页码：1772 / 1776

页数：5

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