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4 juin 2026: 1 événement
séminaire
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Séminaires scientifiques 2026
En savoir plus : Séminaires scientifiques 2026Jeudi 4 juin de 12h30 à 14h00 - Caiyi Xiong - LIAS, Poitiers Séminaire "Real time data driven model learning of complex dynamical systems application to high-speed rotating machines operated with active magnetic bearing" Résumé : Active Magnetic Bearings (AMB) are widely used in high-speed rotating machines due to their ability to levitate rotors without mechanical contact. The considered AMB-supported rotor system is a multivariable system that is open-loop unstable, which makes system identification particularly challenging and requires identification to be performed in closed loop. This article aims at developing data-driven identification methods to track the evolving dynamics of AMB systems in real time, with the objective of detecting performance degradation and anticipating potential failures.
At the current stage of the research, the system is assumed to be time-invariant and the objective is to obtain an initial characterization of its dynamic behavior, in particular the resonance and anti-resonance information. For this purpose, a nonparametric identification is carried out in the frequency domain. Multisine excitation signals are applied to the system and only steady-state responses are retained. Several estimators were evaluated, and the Errors-In-Variables (EIV) estimator was selected to estimate the frequency response Gk. This step provides an accurate nonparametric representation of the system dynamics. Based on this result, future work can be extended to the identification of parametric models.Lieu : Salle Chaussey au H9 (ECL) - Lien Zoom transmis par email.