Fault diagnosis of a class of singular nonlinear systems

Lina Yao; Hong Wang

Fault diagnosis of a class of singular nonlinear systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained. Copyright © 2006 IFAC.

Original language	English
Title of host publication	IFAC Proceedings Volumes (IFAC-PapersOnline)\|IFAC Proc. Vol. (IFAC-PapersOnline)
Pages	42-47
Number of pages	5
Volume	6
Publication status	Published - 2006
Event	6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006 - Beijing Duration: 1 Jul 2006 → …

Conference

Conference	6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006
City	Beijing
Period	1/07/06 → …

Keywords

Adaptive update rules
Fault detection
Fault diagnosis

Cite this

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title = "Fault diagnosis of a class of singular nonlinear systems",

abstract = "A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained. Copyright {\textcopyright} 2006 IFAC.",

keywords = "Adaptive update rules, Fault detection, Fault diagnosis",

author = "Lina Yao and Hong Wang",

year = "2006",

language = "English",

isbn = "9783902661142",

volume = "6",

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booktitle = "IFAC Proceedings Volumes (IFAC-PapersOnline)|IFAC Proc. Vol. (IFAC-PapersOnline)",

note = "6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006 ; Conference date: 01-07-2006",

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T1 - Fault diagnosis of a class of singular nonlinear systems

AU - Yao, Lina

AU - Wang, Hong

PY - 2006

Y1 - 2006

N2 - A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained. Copyright © 2006 IFAC.

AB - A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained. Copyright © 2006 IFAC.

KW - Adaptive update rules

KW - Fault detection

KW - Fault diagnosis

M3 - Conference contribution

SN - 9783902661142

VL - 6

SP - 42

EP - 47

BT - IFAC Proceedings Volumes (IFAC-PapersOnline)|IFAC Proc. Vol. (IFAC-PapersOnline)

T2 - 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006

Y2 - 1 July 2006

ER -

Fault diagnosis of a class of singular nonlinear systems

Abstract

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Keywords

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