State estimation of two-time scale multiple models with unmeasurable premise variables. Application to biological reactors

Anca Maria Nagy (1) , Benoît Marx (1) , Gilles Mourot (1) , Georges Schutz (2) , José Ragot (1)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 LTI - Laboratoire des Technologies Industrielles et Matériaux

This paper deals with the problem of the state estimation of a nonlinear system. The system under study is characterized by a two-time scale model. The state estimation is performed by designing a proportional integral observer (PIO) with unknown inputs. In order to design such an observer, the nonlinear system is transformed into an equivalent multiple model form and the fast dynamics are considered as unknown inputs. An application to an ASM1 model of Wastewater Treatment Plants (WWTP) is considered and the obtained numerical results show the performances of the proposed approach.

Mots clés: Estimation; Nonlinear systems; LMIs

Domaines: Automatique / Robotique

Anca Maria Nagy, Benoît Marx, Gilles Mourot, Georges Schutz, José Ragot. State estimation of two-time scale multiple models with unmeasurable premise variables. Application to biological reactors. 49th IEEE Conference on Decision and Control, CDC 2010, Dec 2010, Atlanta, United States. ⟨10.1109/CDC.2010.5718035⟩. ⟨hal-00547325⟩