Robust adaptive estimation in the competitive chemostat. (2nd November 2020)
- Record Type:
- Journal Article
- Title:
- Robust adaptive estimation in the competitive chemostat. (2nd November 2020)
- Main Title:
- Robust adaptive estimation in the competitive chemostat
- Authors:
- Reis de Souza, Alex
Gouzé, Jean-Luc
Efimov, Denis
Polyakov, Andrey - Abstract:
- Abstract: 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.
- Is Part Of:
- Computers & chemical engineering. Volume 142(2020)
- Journal:
- Computers & chemical engineering
- Issue:
- Volume 142(2020)
- Issue Display:
- Volume 142, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 142
- Issue:
- 2020
- Issue Sort Value:
- 2020-0142-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11-02
- Subjects:
- State estimation -- Chemostat -- Monitoring -- Adaptive
Chemical engineering -- Data processing -- Periodicals
660.0285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00981354 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compchemeng.2020.107030 ↗
- Languages:
- English
- ISSNs:
- 0098-1354
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.664000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14358.xml