Reference : Robust Subspace Identification of a Nonlinear Satellite Using Model Reduction
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/192797
Robust Subspace Identification of a Nonlinear Satellite Using Model Reduction
English
Dossogne, Tilàn mailto [Université de Liège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Noël, Jean-Philippe mailto [Université de Liège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Kerschen, Gaëtan mailto [Université de Liège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Jan-2016
Proceedings of the International Modal Analysis Conference (IMAC) XXXIV
No
International
International Modal Analysis Conference (IMAC) XXXIV
du 25 janvier au 28 janvier 2016
Society for Experimental Mechanics (SEM)
Orlando
FL
[en] subspace method ; nonlinear system identification ; satellite ; spurious poles ; nonsmooth nonlinearities ; spacecraft
[en] The frequency-domain nonlinear subspace identification (FNSI) method has recently been successfully applied to large-scale nonlinear structures. One of the key features of FNSI is the nonlinear generalisation of the stabilisation diagram. However, as in linear system identification, the selection of the model order in the diagram is complicated by the presence of spurious poles, resulting from noise and modelling errors. Spurious poles have been shown to strongly perturb the estimation of the nonlinear coefficients. The present paper establishes a constructive procedure to discriminate between spurious and genuine poles. This procedure is derived in modal space and is based on a dominancy index and on model reduction techniques. It is demonstrated on a complete satellite structure possessing nonsmooth nonlinearities and high modal density. Spurious frequency variations in the nonlinear coefficients are proved to be effectively removed, significantly improving the quality of the overall identified model.
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA ; Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/192797

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