LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System

LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System

This paper presents a diagnosis scheme based on a linear matrix inequality (LMI) algorithm for incipient faults in a nonlinear system class with unknown input disturbances. First, the nonlinear system is transformed into two subsystems, one of which is unrelated to the disturbances. Second, for the...

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Main Authors: Chang-fan Zhang, Min Yan, Jing He, Cheng Luo
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2012/528932
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spelling doaj-81c2f63fb98d4af78c1b405cf0b81c4a2020-11-24T22:50:19ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/528932528932LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear SystemChang-fan Zhang0Min Yan1Jing He2Cheng Luo3College of Electrical and Information Engineering, Hunan University of Technology, Hunan, Zhuzhou 412008, ChinaCollege of Electrical and Information Engineering, Hunan University of Technology, Hunan, Zhuzhou 412008, ChinaCollege of Electrical and Information Engineering, Hunan University of Technology, Hunan, Zhuzhou 412008, ChinaWind Power Department, CSR Zhuzhou Institute Co., Ltd., Hunan, Zhuzhou 412001, ChinaThis paper presents a diagnosis scheme based on a linear matrix inequality (LMI) algorithm for incipient faults in a nonlinear system class with unknown input disturbances. First, the nonlinear system is transformed into two subsystems, one of which is unrelated to the disturbances. Second, for the subsystem that is free from disturbances, a Luenberger observer is constructed; a sliding mode observer is then constructed for the subsystem which is subjected to disturbances, so that the effect of the unknown input disturbances is eliminated. Together, the entire system achieves both robustness to disturbances and sensitivity to incipient faults. Finally, the effectiveness and feasibility of the proposed method are verified through a numerical example using a single-link robotic arm.http://dx.doi.org/10.1155/2012/528932
collection DOAJ
language English
format Article
sources DOAJ
author Chang-fan Zhang
Min Yan
Jing He
Cheng Luo
spellingShingle Chang-fan Zhang
Min Yan
Jing He
Cheng Luo
LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
Journal of Applied Mathematics
author_facet Chang-fan Zhang
Min Yan
Jing He
Cheng Luo
author_sort Chang-fan Zhang
title LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
title_short LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
title_full LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
title_fullStr LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
title_full_unstemmed LMI-Based Sliding Mode Observers for Incipient Faults Detection in Nonlinear System
title_sort lmi-based sliding mode observers for incipient faults detection in nonlinear system
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2012-01-01
description This paper presents a diagnosis scheme based on a linear matrix inequality (LMI) algorithm for incipient faults in a nonlinear system class with unknown input disturbances. First, the nonlinear system is transformed into two subsystems, one of which is unrelated to the disturbances. Second, for the subsystem that is free from disturbances, a Luenberger observer is constructed; a sliding mode observer is then constructed for the subsystem which is subjected to disturbances, so that the effect of the unknown input disturbances is eliminated. Together, the entire system achieves both robustness to disturbances and sensitivity to incipient faults. Finally, the effectiveness and feasibility of the proposed method are verified through a numerical example using a single-link robotic arm.
url http://dx.doi.org/10.1155/2012/528932
work_keys_str_mv AT changfanzhang lmibasedslidingmodeobserversforincipientfaultsdetectioninnonlinearsystem
AT minyan lmibasedslidingmodeobserversforincipientfaultsdetectioninnonlinearsystem
AT jinghe lmibasedslidingmodeobserversforincipientfaultsdetectioninnonlinearsystem
AT chengluo lmibasedslidingmodeobserversforincipientfaultsdetectioninnonlinearsystem
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