State Estimation for Linear Discrete-Time Systems with Unknown Input Using Nonparametric Technique

被引：0
|
作者：
Smagin, V. [1 ]
Koshkin, G. [2 ]
Udod, V. [3 ]
机构：
[1] Tomsk State Univ, Dept Appl Math & Cybernet, Tomsk, Russia
[2] Tomsk State Univ, Dept Appl Math & Cybernet, Lab Geol Informat Comp Sci Dept, Tomsk, Russia
[3] Tomsk State Univ, Dept Econ, Tomsk, Russia
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL APPLICATIONS (CISIA 2015) | 2015年 / 18卷
关键词：
kalman filter; discrete linear systems; unknown input; unknown parameters; filtering algorithm; nonparametric estimators;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper addressed the filtering problems with using nonparametric algorithms for discrete linear systems with the known control input, unknown input and parameters. The designed algorithms are based on combining the Kalman filter and nonparametric estimator. Examples are given to illustrate the usefulness of the proposed approach.
引用
收藏
页码：675 / 677
页数：3
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