Identification of nonlinear dynamic models of electrostatically actuated MEMS

Céline Casenave (1) , Emmanuel Montseny (2) , Henri Camon (3)

1 LAAS-MRS
2 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite
3 LAAS-N2IS - Équipe Nano Ingénierie et Intégration des Systèmes

This paper focuses on the identification of nonlinear dynamic models for physical systems such as electrostatically actuated micro-electro-mechanical systems (MEMS). The proposed approach consists in transforming, by means of suitable global operations, the input-output differential model in such a way that the new equivalent formulation is well adapted to the identification problem, thanks to the following properties: first, the linearity with respect to the parameters to be identified is preserved, second, the continuous dependence on noise measurements is restored. Consequently, a simple least-square resolution can be used, in such a way that some of the difficulties classically encountered with identification methods are by-passed. The method is implemented on real measurement data from a physical system.

Mots clés: Dynamic models; Parameters identification; Least-squares identification; Time-continuous identification; Electrostatically actuated micro-electro-mechanical systems

Domaines: Automatique

Céline Casenave, Emmanuel Montseny, Henri Camon. Identification of nonlinear dynamic models of electrostatically actuated MEMS. Control Engineering Practice, 2010, 18 (8), pp.954-969. ⟨10.1016/j.conengprac.2010.04.002⟩. ⟨hal-00833046⟩