Active adaptive combustion control using neural networks

Combustion science and technology

Volumn 156, Issue 1-6, 2000, Pages 25-47

  Blonbou, R ^a   Laverdant, A ^a   Zaleski, S ^b   Kuentzmann, P ^a  

^a ONERA   (France)

^b CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPUTER SIMULATION; FEEDBACK CONTROL; FUEL BURNERS; NEURAL NETWORKS;

ACTIVE ADAPTIVE COMBUSTION CONTROL; COMBUSTION INSTABILITIES; INTERNAL MODEL CONTROL SYSTEM; RIJKE TUBE BURNER;

COMBUSTION;

EID: 0033646185     PISSN: 00102202     EISSN: None     Source Type: Journal    
DOI: 10.1080/00102200008947295     Document Type: Article

References (28)

1. Billoud G., Galland M.A., Huynh-huu C. and Candel S.M. (1992) Adaptive active control of combustion instabilities. Combust. Sci. and Tech., Vol. 81, pp. 257-283.
2. Bishop C.M. (1995) Neural networks for pattern recognition, Clarendon press OXFORD.
3. Bloxsidge G.J., Dowling A.P., Hooper N. and Langhorne P.J. (1987) Active control of reheat buzz. In AIAA 25th Aerospace Sciences Meeting.
4. Crocco L. and Cheng S.I. (1956) Theory of combustion instability in liquid propellant rocket motors. AGARDOGRAPH, No 8, Butterworths Science Publications, London.
5. Dines P.J. (1984) Active control of flame noise. Ph. D., Cambridge University.
6. Ffowcs-Williams J.E. and Huang X.Y. (1989) Active stabilization of compressor surge. Journal of Fluid Mechanics, pp. 245-262.
7. Heckl M.A. (1985) Active control of the noise from a Rijke tube. In IUTAM, Symposium on Aero and Hydro-Acoustics, pp. 211-216.
8. Hornik K., Stinchcombe M. and White H. (1989) Multilayer feedforward networks are universal approximators. Neural networks. vol. 2, pp. 359-366.
9. o 6 pp. 1083-1112.
10. Huynh-Huu C., Le Helley P., Poinsot T. Esposito E. and Candel S.M. (1993) Contrôle actif adaptatif des instabilités de combustion. Rapport final de synthèse Contrat DRET 89-262 30 Juin 1993, Laboratoire E.M2.C. C.N.R.S., École Centrale Paris.
11. Kim S.I. (1989) Nonlinear combustion instabilities in combustion chambers. Ph. D. Thesis in mechanical engineering. Pennsylvania State University.
12. Lang W., Poinsot T. and Candel S. (1987) Active control of combustion instabilities. Combustion and Flame, vol. 70, pp. 281-289.
13. Laverdant A. (1991) Contribution à l'étude des instabilités de combustion des foyers aérobies. Thèse d'état, Université de Rouen Haute Normandie, ONERA.
14. Marble F.E. and Cox D.W. Jr. (1953) Servo-stabilization of low-frequency oscillations in a liquid bipropellant rocket motors. American Rocket Society Journal, pp. 63-81.
15. McManus K.R., Poinsot T. and Candel S.M. (1993) A review of active control of combustion instabilities. Prog. Energy Combust. Sci., vol 19, pp. 1-29.
16. Nerrand O., Roussel-Ragot P., Personnaz L. and Dreyfus G. (1993) Neural networks and non-linear adaptive filtering: Unifying concepts and new algorithms. Neural computation vol. 5. pp. 165-197.
17. o 96-0758. January 1996.
18. Nguyen D.H. (1991) Application of neural networks in adaptative control. Ph. D. thesis, Stanford University.
19. Pineda F.J. (1989) Recurrent backpropagation and the dynamical approach to adaptive neural computation. Neural comp. Vol. 1, pp. 161-172.
20. o 87-1876.
21. Raun R.L., Beckstead M.W., Finlinson J.C. and Brooks K.P. (1993) A review of Rjke tubes, Rijke burners and related devices, Prog. Energy Combust. Sci., vol. 19, pp. 313-364.
22. lord Rayleigh J.W.S., (1878), The explanation of certain acoustical phenomena, Royal institute proceedings vol. VIII, pp. 536-542.
23. Rijke P.L. (1859) Phil. Mag., Vol. 17, p 419.
24. Rivals I., Personnaz L. and Dreyfus G. (1995) Modélisation, classification et commande par réseaux de neurones: Principes fondamentaux, méthodologie de conception et illustrations industrielles. Les réseaux de neurones pour la modélisation et la commande de procédés, J.P. Corriou, coordinateur (Lavoisier Tec et Doc. 1995).
25. Rumelhart D.E., Hinton G.E. and Williams R.J. (1986) Learning internal representations by error propagation. In Parallel distributed processing: Explorations in the microstructure of cognition. D.E. Rumelhart, J.L. McClelland and the PDP research group (editors). Vol. I: Foundations. MIT Press. Cambridge, Mass.
26. o 22, pp. 256-263.
27. Urbani D., Roussel-Ragot P., Personnaz L. and Dreyfus G. (1993) The selection of neural models of non linear dynamical systems by statistical tests. Neural networks for signal processing IV, pp. 229-237 (IEEE).
28. Widrow B. (1971) Adaptative filters. Aspects of network and System Theory, Holt Rinehart Winston, New-York.