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Nonlinear identification of aircraft gas-turbine dynamics

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Resumo(s)

Identi cation results for the shaft-speed dynamics of an aircraft gas turbine, under normal operation, are presented. As it has been found that the dynamics vary with the operating point, nonlinear models are employed. Two di7erent approaches are considered: NARX models, and neural network models, namely multilayer perceptrons, radial basis function networks and B-spline networks. A special attention is given to genetic programming, in a multiobjective fashion, to determine the structure ofNARMAX and B-spline models.

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

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Ruano, A. E.; Fleming, P. J.; Teixeira, C.; Rodriguez-Vázquez, K.; Fonseca, C. M. Nonlinear identification of aircraft gas-turbine dynamics, Neurocomputing, 55, 3-4, 551-579, 2003.

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