Robust two-stage Kalman filters for systems with unknown inputs

被引：246

作者：

Hsieh, CS ^{[1
]}

机构：

[1] Ind Technol Res Inst, Mech Ind Res Labs, Hsinchu 310, Taiwan

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2000年 / 45卷 / 12期

关键词：

minimum variance; robust filter; two-stage Kalman filter; unbiased filter; unknown input decoupling;

D O I：

10.1109/9.895577

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 new method is developed for the state estimation of linear time-varying discrete systems with unknown inputs. By making use of the two-stage Kalman filtering technique and a new proposed unknown inputs filtering technique, a robust two-stage Kalman filter (RTSKF) which is unaffected by the unknown inputs can be readily derived and serves as an alternative to the Kitanidis' unbiased minimum-variance filter. The application of this new filter is illustrated by optimal filtering for systems with unknown inputs.

引用

页码：2374 / 2378

页数：5

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