Dynamical model identification of population of oysters for water quality monitoring

Hafiz Ahmed 1 Rosane Ushirobira 2, 1 Denis Efimov 3, 1 Damien Tran 4 Jean-Charles Massabuau 4
1 NON-A - Non-Asymptotic estimation for online systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
3 SyNeR - Systèmes Non Linéaires et à Retards
CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : The measurements of valve activity in a population of bivalves under natural environmental conditions (16 oysters in the Bay of Arcachon, France) are used for a physiological model identification. A nonlinear auto-regressive exogenous (NARX) model is designed and tested. The model takes into account the influence of environmental conditions using measurements of the sunlight intensity, the moonlight and tide levels. A possible influence of the internal circadian/circatidal clocks is also analyzed. Through this application, it is demonstrated that the developed dynamical model can be used for estimation of the normal physiological rhythms of permanently immersed oysters and considered for detection of perturbations of these rhythms due to changes in the water quality, i.e. for ecological monitoring.
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Hafiz Ahmed, Rosane Ushirobira, Denis Efimov, Damien Tran, Jean-Charles Massabuau. Dynamical model identification of population of oysters for water quality monitoring. Proc. European Control Conference (ECC) 2014, Jun 2014, Strasbourg, France. ⟨hal-00986038⟩

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