Title : ( Sensor fault detection in a class of nonlinear systems using modal Kalman filter )
Authors: Fatemeh Honarmand , Naser Pariz , Mohammad Bagher Naghibi Sistani ,Access to full-text not allowed by authors
Abstract
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 state estimation 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.
Keywords
Kalman filter Modal Kalman filter State estimation Sensor fault detection Nonlinear systems@article{paperid:1080719,
author = {Honarmand , Fatemeh and Pariz, Naser and Naghibi Sistani, Mohammad Bagher},
title = {Sensor fault detection in a class of nonlinear systems using modal Kalman filter},
journal = {ISA Transactions},
year = {2020},
volume = {107},
month = {December},
issn = {0019-0578},
pages = {214--223},
numpages = {9},
keywords = {Kalman filter
Modal Kalman filter
State estimation
Sensor fault detection
Nonlinear systems},
}
%0 Journal Article
%T Sensor fault detection in a class of nonlinear systems using modal Kalman filter
%A Honarmand , Fatemeh
%A Pariz, Naser
%A Naghibi Sistani, Mohammad Bagher
%J ISA Transactions
%@ 0019-0578
%D 2020