Simplification techniques for EKF computations in fault diagnosis - suboptimal gains

被引：11

作者：

Chang, CT ^{[1
]}

Hwang, JI ^{[1
]}

机构：

[1] Natl Cheng Kung Univ, Dept Chem Engn, Tainan 70101, Taiwan

来源：

CHEMICAL ENGINEERING SCIENCE | 1998年 / 53卷 / 22期

关键词：

fault diagnosis; extended Kalman filter; suboptimal gains;

D O I：

10.1016/S0009-2509(98)00208-5

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The extended Kalman filter (EKF) is one of the most popular model-based techniques for fault detection and diagnosis. In the present study, the idea of suboptimal EKF is utilized to enhance computation efficiency without sacrificing diagnostic accuracy. In particular, a simple procedure is developed to decompose the filter model according to the precedence order of the state/parameter estimation process. As a result, a large portion of the computations needed for propagating error covariances and updating state estimates can be neglected. Extensive simulation results are also presented to demonstrate the effectiveness of these proposed techniques. (C) 1998 Elsevier Science Ltd. All rights reserved.

引用

页码：3853 / 3862

页数：10

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