Robust fault reconstruction via learning observers in linear parameter-varying systems subject to loss of actuator effectiveness

In this study, the problem of robust fault reconstruction in polytopic linear parameter-varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fau...

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Published inIET control theory & applications Vol. 8; no. 1; pp. 42 - 50
Main Authors Jia, Qingxian, Chen, Wen, Zhang, Yingchun, Chen, Xueqin
Format Journal Article
LanguageEnglish
Published Stevenage The Institution of Engineering and Technology 01.01.2014
John Wiley & Sons, Inc
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ISSN1751-8644
1751-8652
DOI10.1049/iet-cta.2013.0417

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Abstract In this study, the problem of robust fault reconstruction in polytopic linear parameter-varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time-varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H∞ techniques. A systematic design of the LO is effectively solved using standard linear-matrix-inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault-reconstruction approach.
AbstractList In this study, the problem of robust fault reconstruction in polytopic linear parameter-varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time-varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H sub( infinity ) techniques. A systematic design of the LO is effectively solved using standard linear-matrix-inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault-reconstruction approach.
In this study, the problem of robust fault reconstruction in polytopic linear parameter-varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time-varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H^sub ∞^ techniques. A systematic design of the LO is effectively solved using standard linear-matrix-inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault-reconstruction approach. [PUBLICATION ABSTRACT]
In this study, the problem of robust fault reconstruction in polytopic linear parameter‐varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time‐varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H∞ techniques. A systematic design of the LO is effectively solved using standard linear‐matrix‐inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault‐reconstruction approach.
In this study, the problem of robust fault reconstruction in polytopic linear parameter‐varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time‐varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H ∞ techniques. A systematic design of the LO is effectively solved using standard linear‐matrix‐inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault‐reconstruction approach.
Author Zhang, Yingchun
Jia, Qingxian
Chen, Xueqin
Chen, Wen
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Issue 1
Keywords fault diagnosis
actuator effectiveness
fault detection
fault signal reconstruction
H∞ control
systematic design
dynamic error system
polytopic LO convergence
satellite system
time-varying faults
actuators
linear matrix inequalities
system state estimation
H∞ techniques
attitude control
robust control
external disturbances
Lyapunov stability theory
polytopic linear parameter-varying systems
fault alarm
learning observers
standard linear-matrix-inequality techniques
linear systems
learning systems
actuator fault reconstruction
polytopic LO stability
robust fault reconstruction
observers
Lyapunov methods
Language English
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Snippet In this study, the problem of robust fault reconstruction in polytopic linear parameter-varying systems, subject to loss of actuator effectiveness and external...
In this study, the problem of robust fault reconstruction in polytopic linear parameter‐varying systems, subject to loss of actuator effectiveness and external...
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SubjectTerms actuator effectiveness
actuator fault reconstruction
Actuators
attitude control
dynamic error system
external disturbances
fault alarm
fault detection
fault diagnosis
fault signal reconstruction
H∞ control
H∞ techniques
learning observers
learning systems
linear matrix inequalities
linear systems
Lyapunov methods
Lyapunov stability theory
observers
polytopic linear parameter‐varying systems
polytopic LO convergence
polytopic LO stability
robust control
robust fault reconstruction
satellite system
standard linear‐matrix‐inequality techniques
system state estimation
systematic design
time‐varying faults
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Title Robust fault reconstruction via learning observers in linear parameter-varying systems subject to loss of actuator effectiveness
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