Wiener-Haar expansion for the modeling and prediction of the dynamic behavior of selfexcited nonlinear uncertain systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Dynamic Systems, Measurement, and Control Année : 2012

Wiener-Haar expansion for the modeling and prediction of the dynamic behavior of selfexcited nonlinear uncertain systems

Sébastien Berger
Evelyne Aubry
  • Fonction : Auteur
  • PersonId : 932944

Résumé

This paper deals with the modeling and prediction of the dynamic behaviour of uncertain nonlinear systems. An efficient method is proposed to treat these problems. It is based on the Wiener-Haar chaos concept resulting from the polynomial chaos theory and it generalizes the use of the multi-resolution analysis well known in the signal processing theory. The method provides a powerful tool to describe stochastic processes as series of orthonormal piecewise functions whose weighting coefficients are identified using the Mallat pyramidal algorithm. This paper shows that the Wiener-Haar model allows an efficient description and prediction of the dynamic behaviour of nonlinear systems with probabilistic uncertainty in parameters. Its contribution- compared to the representation using the generalized polynomial chaos model, is illustrated by evaluating the two models via their application to the problems of the modeling and prediction of the dynamic behaviour of a self-excited uncertain nonlinear system.
Fichier non déposé

Dates et versions

hal-00851989 , version 1 (19-08-2013)

Identifiants

Citer

Lyes Nechak, Sébastien Berger, Evelyne Aubry. Wiener-Haar expansion for the modeling and prediction of the dynamic behavior of selfexcited nonlinear uncertain systems. Journal of Dynamic Systems, Measurement, and Control, 2012, 134 (15), pp.1-11. ⟨10.1115/1.4006371⟩. ⟨hal-00851989⟩
32 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More