Online learning neural architectures and cross-correlation analysis for actuator failure detection and identification

International Journal of Control

Volumn 63, Issue 3, 1996, Pages 433-455

  Napolitano, Marcello R ^a   Casdorph, Van ^a   Neppach, Charles ^a   Naylor, Steve ^a   Innocenti, Mario ^b   Silvestri, Giovanni ^b  

^a West Virginia University   (United States)

^b UNIVERSITY OF PISA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

AIRCRAFT; ALGORITHMS; FAILURE ANALYSIS; LEARNING SYSTEMS; NEURAL NETWORKS; SIMULATION;

ACTUATOR FAILURE DETECTION; NONLINEAR DYNAMIC SIMULATION;

ACTUATORS;

EID: 0030086201     PISSN: 00207179     EISSN: 13665820     Source Type: Journal    
DOI: 10.1080/00207179608921851     Document Type: Article

References (25)

1. Barnard, E., 1992, Optimization for training neural nets. IEEE Transactions on Neural Networks, 3, 232.
2. Brumbaugh, R. W., 1991, An aircraft model for the AIAA controls design challenge. NASA Contractor Report 186019.
3. Chen, C. L., and Nutter, R. S., 1992, An extended back-propagation learning algorithm by using heterogenous processing units. Proceedings of the International Joint Conference on Neural Network (IJCNN’92), Baltimore, Maryland, U.S.A.
4. Cybenko, G., 1989, Approximation by superposition of sigmoidal functions. Mathematics of Control Signals and Systems, 2, 303-314.
5. De Villiers, J., and Barnard, E., 1993, Back-propagation neural nets with one and two hidden layers. IEEE Transactions on Neural Networks, 4, 136.
6. Ha, C. M., 1991, Neural network approach to AIAA aircraft control design challenge. Proceedings of the AIAA Guidance, Navigation and Control Conference, New Orleans, Louisiana, U.S.A., August 1991, AIAA Paper 91-2672.
7. Ha, C. M., Wei, Y. P., and Bessolo, J. A., 1992 a, Identification of aircraft dynamical systems via neural networks. 30th Aerospace Sciences Meeting and Exhibit, Reno, Nevada, U.S.A., 1992, AIAA Paper 92-0047; 1992b, AIAA-92-1075: Reconfigurable aircraft flight control system via neural networks. 1992 Aerospace Design Conference, Irvine, CA, February, AIAA Paper 92-1075.
8. Hoak, D. E., Ellison, D. E. and Carlson, J. W., 1960, USAF stability and control datcom. Flight Control Division, Air Force Flight Dynamics Laboratory, Wright-Patterson Air Force Base, Ohio, U.S.A.
9. Kerr, T., 1982, False alarm and correct detection probabilities over a time interval for restricted classes of failure detection algorithms. IEEE Transactions on Information Theory, 20, 619-631.
10. Massoumnia, M. A., Verghese, G. C., and Willsky, A. S., 1989, Failure Detection and Identification. IEEE Transactions on Automatic Control, 34, 316-321.
11. Motyka, P., Bonnics, W., Hall, S., and Wagner, E., 1984, The evaluation of failure detection and isolation algorithms for restructurable control. NASA Contractor Report 177983, pp. 111.
12. Napolitano, M. R., 1989, A new approach to the flight control system reconfiguration following a battle damage and/or a generic failure on a control surface. Ph.D. thesis, School of Mechanical and Aerospace Engineering, Oklahoma State University, U.S.A., December 1989.
13. Napolitano, M. R., and Swaim, R. L., 1991, New technique for aircraft flight control reconfiguration. AIAA Journal of Guidance, Control and Dynamics, 14, 184-190; 1992, New techniques for aircraft flight control reconfiguration. Control and Dynamic Systems, 52, 155-228.
14. Napolitano, M. R., Chen, C. L, and Nutter, R., 1992, Application of a neural observer as state estimator in active vibration control of a cantilevered beam. IOP International Journal on Smart Materials and Structures, 1.
15. Napolitano, M. R., Chen, C. I., and Naylor, S., 1993, Aircraft failure detection and identification using neural networks. AIAA Journal of Guidance, Control and Dynamics, 16, 999-1009.
16. Napolitano, M. R., Naylor, S. M., Casdorph, V. A., and Neppach, C. D., 1994, On-line learning non-linear direct neuro controllers for restructurable control systems. Proceedings of the AIAA Guidance, Navigation, and Control Conference. Scottsdale, Arizona, U.S.A., August 1994, AIAA Paper 94-3643.
17. Nielsen, R. B., 1990, Neurocomputing (Reading, MA: Addison-Wesley).
18. Ogata, K., 1987, Discrete-Time Control Systems (Englewood Cliff’s, NJ: Prentice Hall).
19. Parlos, A. G., Atiya, A. F., and Sunkel, J. W., 1991, Parameter estimation in space systems using recurrent neural networks. Proceedings of the AIAA Guidance, Navigation and Control Conference, New Orleans, Louisiana, U.S.A., August 1991, AIAA Paper 91-2716.
20. Rumelhart, D., and McClelland, J., 1986, Parallel Distributed Processing (Cambridge, Mass: MIT Press).
21. Simpson, P. K., 1990, Artificial Neural System (Fairview Park, New York: Pergamon).
22. Troudet, T., Garg, S., and Merrill, W. C., 1991, Neural network application to aircraft control system design. Proceedings of the AIAA Guidance, Navigation and Control Conference, New Orleans, Louisiana, August 1991, AIAA Paper 91-2715.
23. Widrow, B., and Sterns, S., 1986, Adaptive Signal Processing (Cambridge, Mass: MIT Press).
24. Willsky, A. S., 1976, A survey of several failure detection methods. Automatica, 12(6), 601-611; 1980, Failure detection in dynamic systems. Agard LS-109, Neuilly sur Seine, France, October 1980, pp. 21-216.
25. Willsky, A. S., and Jones, H. L., 1976, A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems. IEEE Transactions on Automatic Control, 21, 108-112.