Application of time-delay neural and recurrent neural networks for the identification of a hingeless helicopter blade flapping and torsion motions
Título del documento: Application of time-delay neural and recurrent neural networks for the identification of a hingeless helicopter blade flapping and torsion motions
Revue: Journal of the Brazilian Society of Mechanical Sciences and Engineering
Base de datos: PERIÓDICA
Número de sistema: 000312296
ISSN: 1678-5878
Autores: 1
Instituciones: 1Universidade de Sao Paulo, Escola de Engenharia, Sao Carlos, Sao Paulo. Brasil
Año:
Periodo: Abr-Jun
Volumen: 27
Número: 2
Paginación: 97-103
País: Brasil
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Experimental
Resumen en inglés System identification consists of the development of techniques for model estimation from experimental data, demanding no previous knowledge of the process. Aeroelastic models are directly influence of the benefits of identification techniques, basically because of the difficulties related to the modelling of the coupled aero- and structural dynamics. In this work a comparative study of the bilinear dynamic identification of a helicopter blade aeroelastic response is carried out using artificial neural networks is presented. Two neural networks architectures are considered in this study. Both are variations of static networks prepared to accomodate the system dynamics. A time delay neural networks (TDNN) for response prediction and a typical recurrent neural networks (RNN) are used for the identification. The neural networks have been trained by Levemberg-Marquardt algorithm. To compare the performance of the neural networks models, generalization tests are produced where the aeroelastic responses of the blade in flapping and torsion motions at its tip due to noisy pitching angle are presented. An analysis in frequency of the signals from simulated and the emulated models are presented. In order to perform a qualitative analysis, return maps with the simulation results generated by the neural networks are presented
Disciplinas: Ingeniería
Palabras clave: Ingeniería de control,
Ingeniería mecánica,
Helicópteros,
Hélices,
Redes neuronales,
Sistemas de control
Keyword: Engineering,
Control engineering,
Mechanical engineering,
Control systems,
Helicopters,
Neural networks,
Helix
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