Robust Adaptive Estimation in the Competitive Chemostat

Dos Reis De Souza, Alex; Gouzé, Jean-Luc; Efimov, Denis; Polyakov, Andrey

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1016/j.compchemeng.2020.107030

Titre :

Robust Adaptive Estimation in the Competitive Chemostat

Auteur(s) :

Dos Reis De Souza, Alex [Auteur correspondant]
Finite-time control and estimation for distributed systems [VALSE]
Gouzé, Jean-Luc [Auteur]
Université Côte d'Azur [UniCA]
Biological control of artificial ecosystems [BIOCORE]
Efimov, Denis [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Polyakov, Andrey [Auteur]

Finite-time control and estimation for distributed systems [VALSE]

Titre de la revue :

Computers & Chemical Engineering

Pagination :

107030

Éditeur :

Elsevier

Date de publication :

2020-11

ISSN :

0098-1354

Mot(s)-clé(s) en anglais :

state estimation
chemostat
monitoring
adaptive

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Automatique / Robotique

Résumé en anglais : [en]

In this paper, the problem of state estimation of a bioreactor containing a single substrate and several competing species is studied. This scenario is well-known as the competition model, in which multiple species compete ...
Lire la suite >In this paper, the problem of state estimation of a bioreactor containing a single substrate and several competing species is studied. This scenario is well-known as the competition model, in which multiple species compete for a single limiting nutrient. Considering the total biomass to be the only available measurement, the challenge is to estimate the concentration of the whole state vector. To achieve this goal, the estimation scheme is built by the coupling of two estimation techniques: an asymptotic observer, which depends solely on the operating conditions of the bioreactor, and a finite-time parameter estimation technique, which drops the usual requirement of the persistence of excitation. The presented methodology achieves the estimation of each competing species and a numerical example illustrates the intended application.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Idex UCA JEDI

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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