KALMAN FILTER-BASED IDENTIFICATION OF UNKNOWN EXOGENOUS INPUT OF STOCHASTIC LINEAR SYSTEMS VIA PSEUDOMEASUREMENT APPROACH

被引：0

作者：

Ohsumi, Akira ^{[1
]}

Kimura, Takuro ^{[2
]}

Kono, Michio ^{[2
]}

机构：

[1] Miyazaki Univ, Grad Sch Engn, Miyazaki 8892192, Japan

[2] Miyazaki Univ, Interdisciplinary Grad Sch Agr & Engn, Miyazaki 8892192, Japan

来源：

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2009年 / 5卷 / 01期

关键词：

Identification; Exogenous input; Pseudomeasurement; Kalman filter; TARGET TRACKING;

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：

In this paper a new approach to identify the unknown parameter of stepwise or impulsive exogenous input to the linear system front the noisy observation data is proposed. The key of the approach is to introduce an additional information about the unknown parameter vector which is called the pseudomeasurement. Augmenting this pseudomeasurement with the original observation data, the identification of unknown. vector as well as the state estimation is performed. The efficacy of the proposed approach is confirmed by simulation studies.

引用

页码：1 / 16

页数：16

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