Diagnosis of process faults and sensor faults in a class of nonlinear uncertain systems

被引：93

作者：

Zhang, Xiaodong ^{[1
]}

Zhang, Qi ^{[1
]}

Sonti, Niharika ^{[1
]}

机构：

[1] Wright State Univ, Dept Elect Engn, Dayton, OH 45435 USA

来源：

JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2011年 / 22卷 / 01期

关键词：

fault detection; fault isolation; fault detectability; robustness; sensor bias; process faults; SLIDING MODE OBSERVER; ISOLATION SCHEME; ACTUATOR;

D O I：

10.3969/j.issn.1004-4132.2011.01.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems. The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators, each corresponding to a particular fault type. Adaptive thresholds for fault detection and isolation are presented. Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived. A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.

引用

页码：22 / 32

页数：11

共 24 条

[1]

BLANKE M, 2006, DIAGNOSIS FAULTTOLER

[2]

Chen J, 2012, ROBUST MODEL BASED F

[3] A sliding mode observer-based strategy for fault detection, isolation, and estimation in a class of Lipschitz nonlinear systems [J].

Chen, Weitian ;

Saif, Mehrdad .

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2007, 38 (12) :943-955

[4] A geometric approach to nonlinear fault detection and isolation [J].

De Persis, C ;

Isidori, A .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2001, 46 (06) :853-865

[5] EFFECT OF MODEL UNCERTAINTY ON FAILURE-DETECTION - THE THRESHOLD SELECTOR [J].

EMAMINAEINI, A ;

AKHTER, MM ;

ROCK, SM .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1988, 33 (12) :1106-1115

[6]

Farrell J. A., 2006, Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches

[7] FAULT-DIAGNOSIS IN DYNAMIC-SYSTEMS USING ANALYTICAL AND KNOWLEDGE-BASED REDUNDANCY - A SURVEY AND SOME NEW RESULTS [J].

FRANK, PM .

AUTOMATICA, 1990, 26 (03) :459-474

[8]

Gertler J., 1998, Fault Detection and Diagnosis in Engineering Systems

[9] Fault diagnosis based on adaptive observer for a class of non-linear systems with unknown parameters [J].

Jiang, B ;

Staroswiecki, M ;

Cocquempot, V .

INTERNATIONAL JOURNAL OF CONTROL, 2004, 77 (04) :415-426

[10] Feedback based adaptive compensation of control system sensor uncertainties [J].

Li, Shanshan ;

Tao, Gang .

AUTOMATICA, 2009, 45 (02) :393-404

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