A review of in-flight detection and identification of aircraft icing and reconfigurable control

Progress in Aerospace Sciences

Volumn 60, Issue , 2013, Pages 12-34

  Caliskan, Fikret ^a   Hajiyev, Chingiz ^a  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Aircraft icing detection; Kalman filter; Neural network; Parameter identification; Reconfigurable control

Indexed keywords

AERODYNAMICS; AIRCRAFT CONTROL; FIGHTER AIRCRAFT; HAZARDS; IDENTIFICATION (CONTROL SYSTEMS); KALMAN FILTERS; METEOROLOGY; NEURAL NETWORKS; PARAMETER ESTIMATION;

AERODYNAMIC SURFACES; AIRCRAFT ICING; DETECTION AND IDENTIFICATIONS; ENVIRONMENTAL SENSOR; IDENTIFICATION TECHNIQUES; IN-FLIGHT DETECTION; RECONFIGURABLE CONTROL; STATISTICAL PROPERTIES;

AIRCRAFT DETECTION;

EID: 84878277716     PISSN: 03760421     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.paerosci.2012.11.001     Document Type: Review

References (94)

1. 〈http://en.wikipedia.org/wiki/Aviation-accidents-and- incidents#Statistics〉.
2. Dillingham L. Aviation safety, preliminary information on aircraft icing and winter operations, GAO, United States Government Accountability Office testimony before the subcommittee on aviation. Committee on Transportation and Infrastructure; 2010.
3. Cole J., Sands W. Statistical study of aircraft icing accidents. In: Fortieth aerospace science meeting and exhibit, AIAA-91-0558, Reno, Nevada, USA; January 7-10, 1991.
4. NASA Aeronautics Safety Investment Strategy, Weather investment recommendations, Technical Report; April 15, 1997.
5. Merret J., Hossain K.N., Bragg M.B. Envelope protection and atmospheric disturbances in icing encounters. In: Fortieth aerospace science meeting and exhibit, AIAA-2002-0814, Reno, Nevada, USA; January 14-17, 2002.
6. Ratvasky T.P., Ranaudo R.J. Icing Effects on aircraft stability and control determined from flight data. In: Thirty-first aerospace sciences meeting and exhibit, AIAA-93-0398, Reno, Nevada, USA; January 1993.
7. Bragg M.B., Perkins W.R., Sarter N.B., Başar T., Voulgaris P.G., Gurbacki H.M., et al. An interdisciplinary approach to inflight aircraft icing safety. In: Thirty-sixth aerospace sciences meeting and exhibit, AIAA-98-0095, Reno, Nevada, USA; January 1998.
8. Bragg M.B., Basar T., Perkins W.R., Selig M.S., Sarter N.B., Voulgaris P.G., et al. Smart icing systems for aircraft icing safety. In: Fortieth aerospace science meeting and exhibit, AIAA-2002-0813, Reno, Nevada, USA; January 14-17, 2002.
9. Miller R.H., Ribbens W.B. The effects of icing on the longitudinal dynamics of an icing research aircraft. In: Thirty-seventh aerospace science meeting and exhibit, AIAA-99-0636, Reno, Nevada, USA; January 29-31, 1999.
10. Ribbens W.B., Miller R.H. Detection of icing and related loss of control effectiveness in regional and corporate aircraft. In: Thirty-seven aerospace science meeting and exhibit, AIAA-99-0637, Reno, Nevada, USA; January 29-31, 1999.
11. Ratvasky T.P., van Zante J.F. In-flight aerodynamic measurements of an iced horizontal tailplane. In: Thirty-seven aerospace science meeting and exhibit, AIAA-99-0638, Reno, Nevada, USA; January 29-31, 1999.
12. Bragg M.B., Hutchison T., Oltman R., Pokhariyal D., Merritt J. Effect of ice accretion on aircraft flight dynamics. In: Thirty-eighth AIAA aerospace sciences meeting and exhibit, AIAA-2000-0360, Reno, Nevada, USA; January 10-13, 2000.
13. J.W. Melody, T. Başar, W.R. Perkins, and P.G. Voulgaris H-infinity parameter identification for in-flight detection of aircraft icing Control Engineering Practice 8 2000 985 1001
14. J.W. Melody, T. Hillbrand, T. Başar, and W.R. Perkins H-Infinity parameter identification for in-flight detection of aircraft icing: the time varying case Control Engineering Practice 9 2001 1327 1335
15. Schuchard E.A., Melody J.W., Başar T., Perkins W.R., Voulgaris P. Detection and classification of aircraft icing using neural networks. In: Thirty-eighth AIAA aerospace sciences meeting and exhibit, AIAA-2000-0361, Reno, NV, USA; January 10-13, 2000.
16. F.T. Lynch, and A. Khodadoust Effects of ice accretions on aircraft aerodynamics Progress in Aerospace Sciences 37 2001 669 767
17. Johnson M.D., Rokhsaz K. Using artificial neural networks and self-organizing maps for detection of airframe icing. In: Atmospheric flight mechanics conference, AIAA-2000-4099, Denver, CO, USA; August 14-17, 2000.
18. Myers T.T., Klyde D.H., Magdaleno R.E. The dynamic icing detection system. In: Thirty-eighth aerospace sciences meeting and exhibit, AIAA-2000-0364, Reno, NV, USA; January 10-13, 2000.
19. Gurbacki M.H., Bragg M.B. Sensing Aircraft icing effects by flap hinge moment measurement. 17th Applied aerodynamic meeting, AIAA-99-3149, Norfolk, VA; June 1999. p. 368-78.
20. M.H. Gurbacki, and M.B. Bragg Sensing aircraft icing effects by unsteady flap hinge-moment measurement Journal of Aircraft 39 3 2001 575 577
21. Melody J.W., Pokhariyal D., Merret J., Başar T., Bragg M.B. Sensor integration for in-flight icing characterization using neural networks. In: Thirty-ninth aerospace science meeting and exhibit, AIAA-2001-0542, Reno, NV, USA; January 8-11, 2001.
22. C.M. Hajiyev, and F. Caliskan Integrated sensor/actuator FDI and reconfigurable control for fault-tolerant flight control system design The Aeronautical Journal 105 1051 2001 525 533
23. Bucak I.O., Caliskan F., Gürleyen F. Fault diagnosis in dynamical systems using artificial neural networks. In: The fourth Turkish symposium on artificial intelligence and neural networks (TAINN'95), TÜBİTAK Marmara Research Center, Türkiye; June 26, 1995.
24. J.P. Sawyer, and S.S. Rao Structural damage detection and identification using fuzzy logic AIAA Journal 38 12 2000 2328
25. A.P. Brown Inflight icing data gathering during routine flight operations-a case study The Aeronautical Journal 105 1051 2001 501 516
26. Caliskan F., Hajiyev C.M., Aykan R. F16 icing identification based on neural networks and extended Kalman filter. In: ATRS'04 Conference, İTÜ, Istanbul, Turkey; July 1-3, 2004.
27. Aykan R., Caliskan F., Hajiyev C.M. F16 icing identification based on neural networks. In: DECOM'04 Conference, International IFAC Workshop, Bansko, Bulgaria; October 3-5 2004. p. 201-6.
28. Caliskan F., Hajiyev C.M., Aykan R. EKF and neural network based aircraft icing identification applied to F16. In: VIII Triennial International SAUM'04 Conference, Belgrade; November 5-6, 2004. p. 98-105.
29. R. Aykan, C.M. Hajiyev, and F. Caliskan Kalman filter and neural network based icing identification applied to A340 aircraft dynamics Aircraft Engineering and Aerospace Technology 77 1 2005 23 33
30. 1 methods; 1999. 〈http://www.researchgate.net/publication/2471852-Identification-Of- Time-Varying-Flight-Dynamics-Parameters-For-Aircraft-Icing-Detection-And- Classification-Using-.-Methods〉.
31. Miller H.R., Ribbens W.B. The effects of icing on the longitudinal dynamics of an icing research aircraft. In: Thirty-seventh AIAA aerospace sciences meeting and exhibit. American Institute of Aeronautics and Astronautics; 1999, Reno, NV, AIAA-99-0636.
32. Miller H.R., Ribbens W.B. Detection of the loss of elevator effectiveness due to aircraft icing. In: Thirty-seventh AIAA aerospace sciences meeting and exhibit. American Institute of Aeronautics and Astronautics; 1999, Reno, NV, AIAA-99-0637.
33. A. Varga Detection and isolation of actuator/surface faults for a large transport aircraft C. Edwards, T. Lombaerts, H. Smaili, Fault tolerant flight control, Lecture notes in control and information science vol. 399 2010 Springer-Verlag Berlin, Heidelberg 423 448
34. Tousi M.M., Khorasani K. Robust observer-based fault diagnosis for an unmanned aerial vehicle. In: IEEE International Systems Conference (SysCon); 2011. p. 428-34.
35. McKillip M.R. Aircraft icing detection system, United States Patent, Patent Number: US 6,304,194, B1; 2001.
36. R.K. Mehra, and J. Peschon An innovations approach to fault detection and diagnosis in dynamic systems Automatica 7 1971 637 640
37. C.M. Gadzhiev (Hajiyev) Dynamic systems diagnosis based on Kalman filter updating sequences Automation and Remote Control 1 1992 147 150
38. C.M. Gadzhiev (Hajiyev) Check of the generalized variance of the Kalman filter updating sequence in dynamic diagnosis Automation and Remote Control 55 8 1994 1165 1169
39. T. Kailath An innovation approach to least-squares estimation. Part II: Linear smoothing in additive white noise IEEE Transactions on Automatic Control 13 6 1968 665-660
40. C.M. Hajiyev, and F. Caliskan Fault diagnosis and reconfiguration in flight control systems 2003 Kluwer Academic Publishers Boston, USA
41. J.S. Bendat, and A.G. Piersol Random data: analysis and measurement procedures 3rd ed. 2000 Wiley-Interscience New York
42. A.S. Willsky A survey of design methods for failure detection systems Automatica 12 1976 601 611
43. Klekis E.A., Nemura A.A. Sequential criterion for Kalman filter innovation sequence shift detection. In: Proceedings of Lith. SSR Ac., Sc., 1983; 2: 115-125 [in Russian].
44. V.S. Pugachov Probability theory and mathematical statistics 1979 Nauka Moscow [in Russian]
45. D.M. Himmelblau Fault detection and diagnosis in chemical and petrochemical processes 1978 Elsevier Scientific Publishing Company New York
46. T.W. Anderson An introduction to multivariate statistical analysis 2nd ed. 1984 John-Wiley & Sons, Inc. New York
47. M.G. Kendall, and A. Stuart 4th ed. The advanced theory of statistic vol. 3 1983 Griffin High Wycombe
48. C.M. Gadzhiev (Hajiyev) Information provision for supervision and control of offshore platforms 1996 Elm Baku In Russian
49. C.M.A. Gadzhiyev (Hajiyev) New method of Kalman filter innovation sequence statistical characteristics checking Engineering Simulation 1 1996 83 91
50. Hajiyev C.M. Approach to fault detection in Kalman filter based on spectral norm of innovation matrix. In: Proceedings of the international conference system identification and control problems, Moscow, Russia; 26-28 September, 2000. p. 1077-85.
51. C. Hajiyev, and F. Caliskan Fault diagnosis and reconfiguration in flight control systems 2nd ed. 2007 Springer Netherlands
52. C. Hajiyev, and A. Okatan Innovation approach to detect the faults in multidimensional dynamic systems Kybernetes 39 1 2010 127 139
53. C. Hajiyev Testing the covariance matrix of the innovation sequence with sensor/actuator fault detection applications International Journal of Adaptive Control and Signal Processing 24 9 2010 717 730
54. C. Hajiyev Sensor and actuator/surface failure detection based on the spectral norm of an innovation matrix W. Zhang, Fault detection 2010 In-Tech Croatia 195 230
55. C. Hajiyev Tracy-Widom distribution based fault detection approach: application to aircraft sensor/actuator fault detection ISA Transactions, The Journal of Automation 51 1 2012 189 197
56. Hajiyev C., Caliskan F., Aykan R EKF and neural network based aircraft icing detection and identification applied to F-16 flight dynamics. In: Proceedings of the European conference for aerospace sciences (EUCASS), 4-7 July, Moscow, Russia; 2005. p. 1-7.
57. C. Hajiyev, A. Aykan, and F. Caliskan Aircraft icing detection, identification and reconfigurable control. Kalman filtering and neural networks approaches 2011 Lambert Academic Publishing Saarbrücken, Germany
58. Schuchard E.A., Melody J.W., Başar T., Perkins W.R., Voulgaris P. Detection and classification of aircraft icing using neural networks. In: Thirty-eightth AIAA aerospace sciences meeting and exhibit, AIAA 2000-0361, Reno, Nevada; January 10-14, 2000.
59. Ying S., Ai J. Detection of aircraft in-flight icing in non-steady atmosphere using artificial neural network. In: IEEE, third international symposium on intelligent information technology and security informatics; 2010. p. 206-11.
60. Z. Zhang, J. Zhang, L. Ye, and Y. Zheng Research on the application of neural network in diaphragm icing sensor fault diagnosis W. Yu, H. He, N. Zhang, Lecture Notes in Computer Science vol. 5551 2009 Springer-Verlag Berlin, Heidelberg 589 600 [ISNN 2009, Part I]
61. Melody J.W., Pokhariyal D., Merret J., Başar T., Perkins W.R., Bragg M.B. Sensor integration for inflight icing characterization using neural networks. In: Thirty-nineth AIAA aerospace sciences meeting and exhibit, AIAA 2001-0542, Reno, Nevada; January 8-11, 2001.
62. Schuchard E.A., Melody J.W., Başar T., Perkins W.R., Voulgaris P. Detection and classification of aircraft icing using neural networks. In: Proceedings of the 38th AIAA aerospace sciences meeting and exhibit, No. AIAA-2000-0361, Reno, NV; 2000.
63. Campa G., Fravolini M.L., Napolitano M.R.A. Library of adaptive neural networks for control purposes. In: IEEE international symposium on computer aided control system design, Glasgow, Scotland, UK; 2002. p. 115-20.
64. F. Caliskan, R. Aykan, and C. Hajiyev Aircraft icing detection, identification, and reconfigurable control based on Kalman filtering and neural networks Journal of Aerospace Engineering 21 2 2008 51 60
65. M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki Diagnosis and fault-tolerant control 2nd ed. 2006 Springer Heidelberg
66. C. Hajiyev, and F. Caliskan Fault diagnosis and reconfiguration in flight control systems 2003 Kluwer Academic Publishers Dordrecht
67. J. Jiang Fault-tolerant control systems - an introductory overview Acta Automatica Sinica 31 1 2005 161 174
68. Zhang Y., Jiang J. Issues on integration of fault diagnosis and reconfigurable control in active fault-tolerant control systems. In: Proceedings of the IFAC SAFEPROCESS, Beijing, China; August 2006. p. 1513-24.
69. I. Hwang, S. Kim, Y. Kim, and C.E. Seah A survey of fault detection, isolation, and reconfiguration methods IEEE Transactions on Control Systems Technology 18 3 2010 636 653
70. C. Edwards, H. Smaili, and T. Lombaerts Fault tolerant flight control, a benchmark challenge 2010 Springer-Verlag Berlin Heidelberg
71. J. Jiang, and X. Yu Fault-tolerant control systems: a comparative study between active and passive approaches Annual Reviews in Control 36 2012 60 72
72. M. Verhaegen, S. Kanev, R. Hallouzi, C. Jones, J. Maciejowski, and H. Smail Fault tolerant flight control - a survey C. Edwards, T. Lombaerts, H. Smaili, Fault tolerant flight control, Lecture Notes in Control and Information Science vol. 399 2010 Springer-Verlag Berlin Heidelberg 47 89
73. G. Ducard, and H.P. Geering Efficient nonlinear actuator fault detection and isolation system for unmanned aerial vehicles Journal of Guidance, Control, and Dynamics 31 1 2008 225 237
74. Hallouzi R. Multiple-model based diagnosis for adaptive fault-tolerant control. PhD thesis, Delft University of Technology; 2008.
75. J. Ru, and X.R. Li Variable-structure multiple-model approach to fault detection, identification, and estimation IEEE Transactions on Control Systems Technology 16 5 2008 1029 1038
76. G.G. Yen, and L.W. Ho Online multiple-model-based fault diagnosis and accommodation IEEE Transactions on Industrial Electronics 50 2 2003 296 312
77. A.J. Calise, N. Hovakimyan, and M. Idan Adaptive output feedback control of nonlinear systems using neural networks Automatica 37 8 2001 1200 1211
78. Calise A.J., Lee S., Sharma M. Direct adaptive reconfigurable control of a tailless fighter aircraft. In: AIAA guidance, navigation and control conference, Boston, MA; 1998. p. 1-10.
79. A. Calise, S. Lee, and M. Sharma Development of a reconfigurable flight control law for tailless aircraft AIAA Journal of Guidance, Control, and Dynamics 24 5 2001 896 902
80. M. Idan, M. Johnson, and A.J. Calise A hierarchical approach to adaptive control for improved flight safety AIAA Journal on Guidance, Control and Dynamics 25 6 2002 1012 1020
81. Idan M., Johnson M., Calise A.J., Kaneshige J. Intelligent aerodynamic/propulsion flight control for flight safety: a nonlinear adaptive approach. In: American control conference, vol. 4; 2001. p. 2918-23.
82. Johnson E.N., Calise A.J. Neural network adaptive control of systems with input saturation. In: American control conference (ACC), Arlington, Virginia, vol 5; June 2001. p. 3527-32.
83. K.A. Wise, J.S. Brinker, A.J. Calise, D.F. Enns, M.R. Elgersma, and P. Voulgaris Direct adaptive reconfigurable flight control for a tailless advanced fighter aircraft International Journal of Robust and Nonlinear Control 9 14 1999 999 1022
84. H. Alwi, and C. Edwards Fault tolerant control using sliding modes with on-line control allocation C. Edwards, T. Lombaerts, H. Smaili, Fault tolerant flight control, Lecture notes in control and information science vol. 399 2010 Springer-Verlag Berlin Heidelberg 247 272
85. Z. Gao, and P. Antsaklis Stability of the pseudo-inverse method for reconfigurable control systems International Journal of Control 53 3 1991 717 729
86. G. Liu, and R.J. Patton Eigenstructure assignment for control systems design 1998 John Wiley & Sons Chichester
87. Davidson J.B., Andrisani D. Lateral-directional eigenvector flying qualities guidelines for high performance aircraft. Technical report, NASA; 1996.
88. Konstantopoulos, I.K., Antsaklis P.J. Eigenstructure assignment in reconfigurable control systems. Technical report. Interdisciplinary Studies of Intelligent Systems; 1996.
89. Belkharraz A.I., Sobel K. Fault tolerant flight control for a class of control surface failures. In: Proceedings of the IEEE American control conference, Los Alamitos, vol. 6; June 2000. p. 4209-13.
90. Y. Zhang, and J. Jiang Integrated design of reconfigurable fault-tolerant control systems Journal of Guidance 24 1 2000 133 136
91. Mignone D. Control and estimation of hybrid systems with mathematical optimization. PhD thesis, Swiss Federal Institute of Technology, ETH; January 2002.
92. Rattan K.S. Evaluation of control mixer concept for reconfiguration of flight control System, In: Proceedings of IEEE; 1985. p. 560-9.
93. Yang Z., Blanke M. Robust control mixer module method for control reconguration. In: Proceedings of American control conference, Chicago, Illinois; 2000. p. 3407-11.
94. C.M. Hajiyev, and F. Caliskan Integrated sensor/actuator FDI and reconfigurable control for fault- tolerant flight control system design The Aeronautical Journal, the Royal Aeronautical Society, England 2001 525 533 September