Autor(es)

F. D. Marques ^[1] ; J. Anderson ^[2]

Afiliação do(s) autor(es)

^[1] Universidade de São Paulo. Escola de Engenharia de São Carlos. Laboratório de Aeroelasticidade, Dinâmica Laboratório de Aeroelasticidade, Dinâmica de Vôo e Controle, LADinC - Brasil

^[2] University of Glasgow. Department of Aerospace Engineering - Ucrânia

• Tipo de documento: Artigo Científico
• Fonte: Journal of the Brazilian Society of Mechanical Sciences; v. 24, n. 1, p. 32-39, 2002-03-00.

Resumo

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime. (AU)

• Processo FAPESP: 97/13323-8 - Controle ativo da resposta aeroelástica em uma asa inteligente
• Beneficiário: Flávio Donizeti Marques
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores