Estimation of Multiple Transient Actuator Faults Using Augmented Error Technique
A fault diagnosis scheme for nonlinear uncertain
dynamic systems with both abrupt and incipient faults is discussed.
An active fault approach is designed that utilizes adaptive laws of
augmented error technique in such a way that accounts for matching
uncertainties and the occurrence of actuator faults. The main idea is
designing the robust fault diagnosis scheme that guarantee stability of
the system in the presence of faults. Using the augmented error
technique from model reference adaptive control, an observation
error model is formulated to give an adaptive diagnostic algorithm
which produces the estimate of actuator faults. Changes in the system
due to faults are modelled as unknown nonlinear functions. An
occurred fault is isolated if the residual associated with the observer
remains below its corresponding adaptive threshold, while at least
one of the components of the residual associated with all other
estimators exceeds its threshold at some finite time. Unknown Input
Observer (UIO) is an estimator which is decoupled from the
unknown inputs (certain disturbances, or faults) that may be acting on
the system. A key design issue of the proposed fault isolation scheme
is the derivation of adaptive residual thresholds associated with
observer. The simulation result indicate that the proposed algorithm
is more realistic, in the sense that better decoupling properties can be
assured without knowledge about unknown inputs, and it is
potentially useful in the development of a fault-tolerant control
Frank, P. M. and Ding, X., “Survey of robust residual generation and
evaluation methods in observer-based fault detection systems”, Journal
of Process Control, 7(6), pp. 403-424,(1997).
Gertler, J, “Fault Detection of DynamicalSystems”, Marcel Dekker, Inc.
Gao, Z. W. and Wang, H. (2006), “Descriptor observer approaches for
multivariable systems with measurement noises and application in fault
detection and diagnosis”. Systems and Control Letters, vol.55, no.4
R. Aarthi and R.Ananda Natarajan,”Observer Based Fault Estimation Of
Uncertainities In A Dynamic System” National Conference Green ICT-
Pondicherry Engg College, Paper ID-GCIT-38
Gertler, J., Staroswiecki, M. and Shen,M. “Direct design of structured
residuals for fault diagnosis in linear systems”. American Control
Conference, Anchorage, Alaska, May2002.
Gertler, J, “Residual Generation in Model Based Fault Diagnosis”.
Control Theory and Advanced Technology, Vol. 9, pp. 259-285 (March
H. Wang and S. Daley, “Actuator Fault Diagnosis: An Adaptive
Observer-Based Technique”. IEEE Transactions On Automatic Control,
VOL. 41, NO. 7, JULY 1996, pg. 1073-1078.
Janos J. Gertler, “Survey of Model-Based Failure Detection and
Isolation in Complex Plants”. IEEE Control Systems Magozrne,
December 1988, PG. 3-11.
R. Isermann, Supervision, “Fault-Detection And Fault Diagnosis
Methods- An Introduction”, Control Eng. Practice, vol.5, no. 5, pp. 639-
J. Wu, G. Biswas, S. Abdelwahed, and E. Manders, “A hybrid control
system design and implementation for a three tank testbed”. In
Proceedings of the 2005 IEEE Conference on Control Applications,
pages 645–650, August2005.
Rolf Isermann, “Model Based Fault Detection And Diagnosis Methods”.
Proceedings of the American control conference, seattle Washington,
june 1995, pg. 1605-1609.
Venkat Venkatasubramanian, Raghunathan Rengaswamy, Surya N.
Kavuri, Kewen Yin, “A review of process fault detection and diagnosis
Part III: Process history based methods”, Computers and Chemical
Engineering 27 (2003), pg. 327-/346.
Venkat Venkatasubramanian, Raghunathan Rengaswamy, Surya N.
Kavuri, “A review of process fault detection and diagnosis Part II:
Qualitative models and search strategies”. Computers and Chemical
Engineering 27 (2003) 313-/326.
Venkat Venkatasubramanian, Raghunathan Rengaswamy, Kewen Yin,
Surya N. Kavuri, “A review of process fault detection and diagnosis Part
I: Quantitative model-based methods”. Computers and Chemical
Engineering 27 (2003) 293-311.
Gao, Z. W., Ding, S. X. and Ma, Y. (2007), “Robust fault estimation
approach and its application in vehicle lateral dynamical systems,
Optimal Control Applications and Methods”. vol.28, no.3, pp. 143-156.
K.S.Narendra and A.M. annaswamy,”Stable Adaptive system”,
eglewood cliffs, NJ, Prentice-hall,1989.
K.J.Astrom and B.wittenmark, Adaptive Control, Reading MA:addision-
Youmin Zhang, Jin Jiang, “Bibliographical review on reconfigurable
fault-tolerant control systems”. Annual Reviews in Control 32 (2008)
Gertler, J. and Staroswiecki, M. “Structured fault diagnosis in mildly
nonlinear systems: Parity space and input-output formulation”. FAC
thWorld Congress, Barcelona, Spain, July 2002.
Gao, Z. W., Breikin, T and Wang, H. (2007), “High-gain estimator and
fault-tolerant design with application to a gas turbine dynamic system”.
IEEE Transactions on Control Systems Technology, vol.15, no.4,
Jianping Maa, Jin Jiang, “Applications of fault detection and diagnosis
methods in nuclear power plants: A review”. Progress in Nuclear Energy
Marlin, E “Process Control: Designing Processes and Control Systems
for Dynamic Performance”. McGraw-Hill International Editions (1995).
R.J. Patton, P. Frank and R. Clark (1989), “Fault Diagnosis in Dynamic
Systems. Theory and applications. Control Engineering Series”. Prentice
Hall ( A new edition in 2000).
A.D. Pouliezos, G.D. Stavrakakis, (1994), “Real time fault monitoring
of industrial processes”. Kluwer Academic Publishers.
J. Chen and R.J. Patton (1999), “Robust model-based fault diagnosis for
dynamic systems”. Kluwer Academic Publishers.
Xiaodong Zhang, Marios Polycarpou, and Thomas Parisini “ Abrupt
and Incipient Fault Isolation of Nonlinear Uncertain Systems”.
Proceedings of the American Control Conference Chicago, Illinois June
, pg. 3713-3717.
Jordi Meseguer, Vicenc¸ Puig, Teresa Escobet, Jordi Saludes, “Observer
gain effect in linear interval observer-based fault detection”. Journal of
Process Control 20 (2010), pg. 944–956.
Yingwei Zhang, S. Joe Qin, “Adaptive actuator fault compensation for
linear systems with matching and unmatching uncertainties”. Journal of
Process Control 19 (2009), pg. 985–990.
Weitian Chen and Mehrdad Saif, “An Actuator Fault Isolation Strategy
for Linear and Nonlinear Systems”. American Control Conference, June
Zhiyuan Wang, Malgorzata M. Marek-Sadowska, Fellow, IEEE, Kun-
Han Tsai, and Janusz Rajski, Associate Member, IEEE, “Delay-Fault
Diagnosis Using Timing Information”. IEEE Transactions On
Computer-Aided Design Of Integrated Circuits And Systems, VOL. 24,
NO. 9, SEPTEMBER 2005, pg. 1315-1325.
KÄoppen-Seliger, B., Alcorta-Garca, E.,Frank P.M., “Fault Detection:
Different strategies for Modelling Applied to the Three tank Benchmark
- A Case Study”. European Control Conference, Karlsruhe, Germany,
S.AbrahamLincon., D.Sivakumar., J.Prakash., ”State and Fault
Parameter Estimation Applied To Three-Tank Bench Mark Relying On
Augmented State Kalman Filter”. ICGSTACSE Journal, Volume 7,
Issue 1, May 2007.
Sunwon Park’ And David M. Himmelblau’, “Fault Detection And
Diagnosis Via Parameter Estimation In Lumped Dynamic Systems”.
American Chemical Society, 1983, 22, Pg. 482-487.
P. Girard, C. Landrault S. Pravossoudovitch, “Reliable Method For
Delay-Fault Diagnosis”, Electronics Letters 26th September 1991 Vol.
No. 2, pg. 1841-1843.
M.A. BinShams, H.M.Budman, T.A.Duever, “Fault detection,
identification and diagnosis using CUSUM based PCA”, Chemical
Engineering Science 66 (2011), pg. 4488–4498.
R. Isermann and P. Balle, “Trends in the application of model-based
fault detection and diagnosis of technical processes”, Control Eng.
Practice, vol. 5, no. 5, pp. 709-719, 1997.
Ron patton, “A benchmark study approach to fault diagnosis of
industrial process control systems”. The IEE Control & Automation
Professional Network, pg. 61-79, June 2005.
Erdal Kiliç, “Fault Detection And Diagnosis In Nonlinear Dynamical
Systems”. Graduate School of Natural and Applied Sciences, AUGUST
, pg. 1-171.
J.H. Kim, Z. Bien, “Geometric approach for fault diagnosis in linear
dynamic control systems”. IEE Proceedings-D, Vol. 138, No. 3, MAY
, pg. 293-302.
F.W.Poon and D.W.Gu, “Fault detection using Luenberger-like
observers”. Proceedings of the 38 Conference on Decision & Control
Woenix, Arizona USA December 1999, pg. 3116-3121.
Stephen.i.gallant, “A connectionist expert system approach to fault
diagnosis in the presence of noise and redundancy”. Iinternational
workshop on artificial intelligence for industrial applications 1988, pg.
Hanlong Yang, “Estimation And Fault Diagnostics In Nonlinear And
Time Delay Systems Based On Unknown Input Observer
Methodology”. National library of Canada, April 1997, pg. 1-155.
P. Kabore and H. Wang, “Design of Fault Diagnosis Filters and Fault-
Tolerant Control for a Class of Nonlinear Systems”. IEEE Transactions
On Automatic Control, VOL. 46, NO. 11, NOVEMBER 2001, pg. 1805-
T.-G.Park, J.-S.Ryu and K.-S.Lee, “Actuator fault estimation with
disturbance Decoupling”, IEE Proc.-Control theory appl. vol.147, No. 5,
September 2005, pg. 501-508.
Edward.y. chow and alan s. willsky, “Analytical Redundancy and the
Design of Robust Failure Detection Systems”. IEEE Transacttons On
Automatic Control, VOL. AC-29, NO. 7. JULY 1984, pg. 603-614.
F. KWATZ, S. BOUSGHIRI, G. MOUROT, “A Finite memory observer
approach to the design of fault detection algorithms”. Proceedings of the
American control conference Baltimore, Maryland, June 1994, pg. 3574-
Albino Martínez-Sibaja, Carlos M. Astorga-Zaragoza, Alejandro
Alvarado-Lassman, Rubén Posada-Gómez, Gerardo Aguila-Rodríguez,
José P. Rodríguez-Jarquin and Manuel Adam-Medina, “Simplified
Interval Observer Scheme: A New Approach for Fault Diagnosis in
Instruments”. Sensors 2011, 11, 612-622; doi:10.3390/s110100612.
Qingsong Yang, “Model-Based And Data Driven Fault Diagnosis
Methods With Applications To Process Monitoring”. Electrical
Engineering and Computer Sciences Case Western Reserve University
May 2004, pg. 1-191.
Weitian chen, “Model Based Fault Diagnosis In Complex Control
Systems- Robust And Adaptive Approaches,School Of Engineering
Science”. April 2007, pg. 1-251.
Salvador de Lira Ramirez, “Model Based Fault Detection and Isolation
for a PEMFC System”. Department of Systems Engineering & Industrial
Automation Universidad Politecnica de Catalunya, pg. 1-125.
Redouane Hallouzi, “Multiple-Model Based Diagnosis for Adaptive
Fault-Tolerant Control”. Dutch Technology Foundation (STW) under
project number 04506, March 2008, pg. 1-188.
A.H.Jones, B.Porter and R.N. fripp, “Qualitative and quantitative
approaches to the diagnosis of plant faults, centre for instrumentation
and automation”. University of Salford, 1989, pg. 87-92.
Stephen D.J.McArthur, “Agent technologies for power system plant
monitoring and diagnosis”. The IEE control & automation professional
network, pg. 51-65.
You Fuqiang, Tian Zuohua, Shi Songjiao, “Robust fault diagnosis for
linear time-delay systems with uncertainty”, 2005 American Control
Conference June 8-10, 2005. Portland, OR, USA, pg. 1666-1671.
Dr. Ron J. Patton, Mr. J. Chen, “Robustness In Quantitative Model-
Based Fault Diagnosis”. Department of Electronics, University of York,
YORK, YO1 SDD, England, pg. 4/1-4/17.
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