Sensor fault detection in a class of nonlinear systems using modal Kalman filter

被引：13

作者：

Honarmand-Shazilehei, Fatemeh ^{[1
]}

Pariz, Naser ^{[1
]}

Sistani, Mohammad B. Naghibi ^{[1
]}

机构：

[1] Ferdowsi Univ Mashhad, Dept Elect Engn, POB 91775-1111, Mashhad, Razavi Khorasan, Iran

来源：

ISA TRANSACTIONS | 2020年 / 107卷

关键词：

Kalman filter; Modal Kalman filter; State estimation; Sensor fault detection; Nonlinear systems; DIAGNOSIS; STRATEGY;

D O I：

10.1016/j.isatra.2020.08.008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Kalman filter and its different variants are commonly used as optimal methods for fault detection in various types of system components. In this paper, a newly introduced type of aforementioned filters, called modal Kalman filter, is extended and utilized in order to estimate the states of nonlinear systems, for sensor fault detection purposes, in a class of nonlinear certain systems. This method, in contrast to the extended Kalman filter, which employs only the linear term of Taylor expansion, retains higher-order terms; as a result, the estimation error will reduce accordingly. Practicality and effectivity of this method, and its superiority over Kalman filter, in terms of accuracy and promptness of sensor fault detection, are also verified with simulation results. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：214 / 223

页数：10

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