This paper proposes a novel fault diagnosis approach for the satellite attitude control system with flywheel faults. The key contributions include fault estimation by sparse approximation algorithm and diagnosis of multiple faults. In this paper, a Taylor series expansion is used to derive a fault estimation representation. Based on the sparse property of the faults, fault estimation is formulated as a sparse approximation problem and solved using the orthogonal matching pursuit (OMP) algorithm. Simulation results demonstrate the effectiveness of the proposed method.

References

1.
Venkateswaran
,
N.
,
Siva
,
M. R.
, and
Goel
,
P. S.
,
2002
, “
Analytical Redundancy Based Fault Detection of Gyroscopes in Spacecraft Applications
,”
Acta Astronaut.
,
50
(
9
), pp.
535
545
.10.1016/S0094-5765(01)00209-0
2.
Patton
,
R. J.
,
Uppala
,
F. J.
,
Simani
,
S.
, and
Polle
,
B.
,
2010
, “
Robust FDI Applied to Thruster Faults of a Satellite System
,”
Control Eng. Pract.
,
18
(
9
), pp.
1093
1109
.10.1016/j.conengprac.2009.04.011
3.
Talebi
,
H. A.
, and
Khorasani
,
K.
,
2007
, “
A Neural Network-Based Actuator Gain Fault Detection and Isolation Strategy for Nonlinear Systems
,”
Proceedings of 46th IEEE Conference on Decision and Control
,
New Orleans, LA
, pp.
2614
2619
.
4.
Talebi
,
H. A.
,
Khorasani
,
K.
, and
Tafazoli
,
S.
,
2009
, “
A Recurrent Neural-Network-Based Sensor and Actuator Fault Detection and Isolation for Nonlinear Systems With Application to the Satellite's Attitude Control Subsystem
,”
IEEE Trans. Neural Network
,
20
(
1
), pp.
45
60
.10.1109/TNN.2008.2004373
5.
Wang
,
J.
,
Jiang
,
B.
, and
Shi
,
P.
,
2008
, “
Adaptive Observer-Based Fault Diagnosis for Satellite Attitude Control Systems
,”
Int. J. Innovative Comput. Inf. Control
,
4
(
8
), pp.
1921
1929
.
6.
Wu
,
Q.
, and
Saif
,
M.
,
2005
, “
Neural Adaptive Observer Based Fault Detection and Identification for Satellite Attitude Control Systems
,”
Proceedings of 2005 American Control Conference
,
Portland, OR
, Vol.
2
, pp.
1054
1059
.
7.
Wu
,
Q.
, and
Saif
,
M.
,
2005
, “
Robust Fault Diagnosis for a Satellite System Using a Neural Sliding Mode Observer
,”
Proceedings of 44th IEEE Conference on Decision and Control
,
Seville, Spain
, pp.
7668
7673
.
8.
Chen
,
W.
, and
Saif
,
M.
,
2007
, “
Observer-Based Fault Diagnosis of Satellite Systems Subject to Time-Varying Thruster Faults
,”
ASME J. Dyn. Syst.
,
129
(
3
), pp.
352
356
.10.1115/1.2719773
9.
Gao
,
Z.
,
Jiang
,
B.
,
Shi
,
P.
, and
Cheng
,
Y.
,
2010
, “
Sensor Fault Estimation and Compensation for Microsatellite Attitude Control Systems
,”
Int. J. Control, Autom.
,
8
(
2
), pp.
228
237
.10.1007/s12555-010-0207-7
10.
Wang
,
Z.
,
Shen
,
Y.
, and
Zhang
,
X.
,
2012
, “
Attitude Sensor Fault Diagnosis Based on Kalman Filter of Discrete-Time Descriptor System
,”
J. Syst. Eng. Electron.
,
23
(
6
), pp.
914
920
.10.1109/JSEE.2012.00112
11.
Li
,
L.
, and
Zhang
,
H.-Y.
,
2006
, “
Controller Reconfiguration Against Reaction Wheel Failure Based on Predictive Filters
,”
Proceedings of 1st International Symposiumon Systems and Control in Aerospace and Astronautics
,
Harbin
, pp.
1245
1249
.
12.
Candès
,
E. J.
,
Romberg
,
J.
, and
Tao
,
T.
,
2006
, “
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
,”
IEEE T. Inform. Theory
,
52
(
2
), pp.
489
509
.10.1109/TIT.2005.862083
13.
Donoho
,
D. L.
,
2006
, “
Compressed Sensing
,”
IEEE Trans. Inf. Theory
,
52
(
4
), pp.
1289
1306
.10.1109/TIT.2006.871582
14.
Candès
,
E. J.
, and
Tao
,
T.
,
2006
, “
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
,”
IEEE Trans. Inf. Theory
,
52
(
12
), pp.
5406
5425
.10.1109/TIT.2006.885507
15.
Bickson
,
D.
,
Baron
,
D.
,
Ihler
,
A.
,
Avissar
,
H.
, and
Dolev
,
D.
,
2011
, “
Fault Identification via Non-Parametric Belief Propagation
,”
IEEE Trans. Signal Process.
,
59
(
6
), pp.
2602
2603
.10.1109/TSP.2011.2116014
16.
Wu
,
Q.
, and
Saif
,
M.
,
2006
, “
Robust Fault Diagnosis for a Satellite Large Angle Attitude System Using an Iterative Neuron PID Observer
,”
Proceedings of 2006 American Control Conference
,
Minneapolis, MN
, pp.
6710
5715
.
17.
Sidi
,
M. J.
,
1997
,
Spacecraft Dynamics and Control: A Practical Engineering Approach
,
Cambridge University Press
,
New York
.
18.
Crassidis
,
J. L.
, and
Markley
,
F. L.
,
1997
, “
Predictive Filtering for Nonlinear Systems
,”
J. Guid. Control Dyn.
20
(
3
), pp.
566
572
.10.2514/2.4078
19.
Li
,
J.
, and
Zhang
,
H.
,
2004
, “
Analysis of Fault Detection Method Based on Predictive Filter Approach
,”
Sci. China, Ser. E
,
34
(
12
), pp.
1375
1392
.10.1360/04yf0224
20.
Shen
,
Y.
,
Zhang
,
Y.
, and
Wang
,
Z.
,
2011
, “
Satellite Fault Diagnosis Method Based on Predictive Filter and Empirical Mode Decomposition
,”
J. Syst. Eng. Electron.
,
22
(
1
), pp.
83
87
.10.3969/j.issn.1004-4132.2011.01.010
21.
Donoho
,
D. L.
,
Elad
,
M.
, and
Temlyakov
,
V. N.
,
2006
, “
Stable Recovery of Sparse Overcomplete Representations in the Presence of Noise
,”
IEEE Trans. Inf. Theory
,
52
(
1
), pp.
6
18
.10.1109/TIT.2005.860430
22.
Tropp
,
J. A.
, and
Gilbert
,
A. C.
,
2007
, “
Signal Recovery From Random Measurements via Orthogonal Matching Pursuit
,”
IEEE Trans. Inf. Theory
,
53
(
12
), pp.
4655
4666
.10.1109/TIT.2007.909108
23.
Needell
,
D.
, and
Vershynin
,
R.
,
2010
, “
Signal Recovery From Incomplete and Inaccurate Measurements via Regularized Orthogonal Matching Pursuit
,”
IEEE J. Sel. Topics Signal Process.
,
4
(
2
), pp.
310
316
.10.1109/JSTSP.2010.2042412
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