Nonlinear identification of aircraft gas-turbine dynamics

Neurocomputing

Volumn 55, Issue 3-4, 2003, Pages 551-579

  Ruano, A E ^a   Fleming, P J ^b   Teixeira, C ^a   Rodriguez Vazquez K ^c   Fonseca, C M ^a  

^a UNIVERSITY OF ALGARVE   (Portugal)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

Author keywords

Gas turbine engines; Genetic programming; Multiobjective optimisation; Neural networks; Nonlinear system identification

Indexed keywords

AIRCRAFT; MATHEMATICAL MODELS; NEURAL NETWORKS; SHAFTS (MACHINE COMPONENTS);

SHAFT-SPEED DYNAMICS;

GAS TURBINES;

FUEL;

AIRCRAFT; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER PROGRAM; CONTROLLED STUDY; DYNAMICS; EQUIPMENT; GAS; HYPERBARISM; HYPOBARISM; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; PRIORITY JOURNAL; STATISTICAL MODEL; VALIDATION PROCESS;

EID: 0344826095     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(03)00393-X     Document Type: Article

References (22)

1. V.Y. Arkov, G.G. Kulikov, T.V. Breikin, P.J. Fleming, Dynamic model identification of gas turbines, in: UKACC International Conference on Control 98, IEE, UK, 1998, pp. 1367-1371.
2. S.A. Billings, S. Chen, R.J. Backhouse, Identification of linear and non-linear models of a turbocharged automotive diesel engine, Mech. Systems Signal Process. 3 (2) (1989) 123-142.
3. S.A. Billings, M.B. Fadzil, The practical identification of systems with non-linearities, in: Proceedings of the Seventh IFAC Symposium on Identification and System Parameter Estimation, York, UK, 1985, pp. 155-160.
4. S.A. Billings, W.S.F. Voon, Correlation based model validity tests for nonlinear models, Int. J. Control 44 (1) (1986) 235-244.
5. A. Borell, C. Evans, D. Rees, Identification of aircraft gas turbine dynamics using frequency-domain techniques, in: UKACC International Conference on Control 98, IEE, UK, 1998, pp. 1372-1378.
6. D. Broomhead, D. Lowe, Multivariable functional interpolation and adaptive networks, Complex Systems 2 (1988) 321-355.
7. M. Brown, C. Harris, Neurofuzzy adaptive modelling and control, Prentice-Hall, London, 1994.
8. C. Cabrita, A.E. Ruano, C.M. Fonseca, Single and multi-objective genetic programming design for B-spline neural networks and neuro-fuzzy systems, in: Proceedings of the IFAC Workshop on Advanced Fuzzy/Neural Control 200 (AFNC'01), Valencia, Spain, 2001, pp. 93-98.
9. C. Chinrungrueng, C.H. Séquin, Optimal adaptive k-means algorithm with dynamic adjustment of learning rate, IEEE Trans. Neural Networks 6 (1) (1995) 157-169.
10. C. Evans, Testing and modelling aircraft gas turbines, in: Proceedings of the UKACC International Conference on Control 98, IEE, UK, 1998, pp. 1361-1366.
11. A. Fink, S. Töpfer, R. Isermann, Neuro and neuro-fuzzy identification for model-based control, in: IFAC Workshop on Advanced Fuzzy-Neural Control, Spain, 2001, pp. 111-116.
12. P.M. Ferreira, E.A. Faria, A.E. Ruano, Neural network models in greenhouse air temperature prediction, Neurocomputing 43 (1) (2002) 51-75.
13. C.M. Fonseca, P.J. Fleming, Multiobjective optimization and multiple constraint handling with evolutionary algorithms-Part 1: a unified formulation, IEEE Trans. Systems Man Cybernet. 28 (1) (1998) 26-37.
14. R. Isermann, S. Ernst, O. Nelles, Identification with dynamic neural networks-architectures, comparisons, applications, Proceedings of the 11th IFAC Symposium on System Identification, Vol. 3, 1997, pp. 997-1022.
15. J.R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, 1992.
16. I.J. Leontaris, S.A. Billings, Input-output parametric models for non-linear systems, Int. J. Control 41 (2) (1985) 311-341.
17. J.P. Norton, P.T. Ladlow, D.C. Hill, Identification of large-transient effects in aircraft gas-turbine dynamics, in: UKACC International Conference on Control 98, IEE, UK, 1998, 1379-1384.
18. K. Rodríguez-Vázquez, P.J. Fleming, Multi-objective genetic programming for nonlinear system identification, Electron. Lett. 34 (9) (1998) 930-931.
19. A.E. Ruano, D. Jones, P.J. Fleming, A new formulation of the learning problem for a neural network controller, in: Proceedings of the IEEE Conference on Decision and Control, Brighton, UK, 1991, pp. 865-866.
20. D. Rumelhart, J. McClelland and the PDP Research Group, Parallel Distributed Processing, Vol. 1, MIT Press, Cambridge, MA, 1986.
21. J. Schoukens, R. Pintelon, Identification of Linear Systems, Pergamon Press, Oxford, 1991.
22. E. Weyer, T. Kavli, The ASMOD algorithm. Some new theoretical and experimental results, SINTEF Report STF31 A95024, Oslo, 1995.