Continuous discrete observer with updated sampling period (long version)

Vincent Andrieu (1, 2) , Madiha Nadri (1) , Ulysse Serres (1) , Jean-Claude Vivalda (3, 4)

1 LAGEP - Laboratoire d'automatique et de génie des procédés
2 Arbeitsgruppe Funktionalanalysis
3 CORIDA - Robust control of infinite dimensional systems and applications
4 IECL - Institut Élie Cartan de Lorraine

This paper is the long version of a published paper in Automatica (and presented to NOLCOS 2013). This paper deals with the design of high gain observers for a class of continuous-time dynamical systems with discrete-time measurements. Indeed, different approaches based on high gain techniques have been followed in the literature to tackle this problem. Contrary to these works, the measurement sampling time is considered to be variable. Moreover, the new idea of the proposed work is to synthesize an observer requiring the less knowledge as possible from the output measurements. This is done by using an updated sampling time observer. The vector fields related to the systems considered in this paper are assumed to be globally Lipschitz. Under this assumption, the asymptotic convergence of the observation error is established. As an application of this approach, a state estimation problem of an academic bioprocess is studied, and its simulation results are discussed.

Mots clés: sampled-data; Nonlinear systems; continuous-discrete time observers; updated sampled-data; high gain observer

Domaines: Automatique / Robotique

Vincent Andrieu, Madiha Nadri, Ulysse Serres, Jean-Claude Vivalda. Continuous discrete observer with updated sampling period (long version). [Research Report] LAGEP CNRS. 2014. ⟨hal-00828578v2⟩