Reference : A stochastic framework for subspace identification of a strongly nonlinear aerospace ...
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/161925
A stochastic framework for subspace identification of a strongly nonlinear aerospace structure
English
Noël, Jean-Philippe mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Schoukens, Johan [Vrije Universiteit Brussel - VUB > ELEC > > >]
Kerschen, Gaëtan mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Feb-2014
Proceedings of the International Modal Analysis Conference (IMAC) XXXII
No
No
International
International Modal Analysis Conference (IMAC) XXXII
du 2 février 2014 au 6 février 2014
SEM
Orlando
FL
[en] System identification ; maximum likelihood ; subspace method ; aerospace structure ; nonsmooth nonlinearities
[en] The present study exploits the maximum likelihood identification framework for deriving statistically-optimal models of nonlinear mechanical systems. The identification problem is formulated in the frequency domain, and model parameters are calculated by minimising a weighted least-squares cost function. Initial values of the model parameters are obtained by means of a nonlinear subspace algorithm. The complete identification methodology is first demonstrated on a Duffing oscillator, prior to being applied to a full-scale aerospace structure.
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/161925

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