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Growth Dynamics of Algal-bacterial Cocultures: A Control Engineering Perspective

Abbadi, M; Spurgeon, S; (2018) Growth Dynamics of Algal-bacterial Cocultures: A Control Engineering Perspective. In: 2018 European Control Conference (ECC). (pp. pp. 2344-2349). IEEE Green open access

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Abstract

Despite internal complexity, algae and bacteria have coexisted since the early stages of evolution. This co- evolution follows relatively simple laws that can be clearly expressed using mathematical models. This paper performs a quantitative analysis, motivated from the perspective of control theory, of a classical model from the literature. The model has been developed using data from an in vivo experimental two-species system where the bacterium Mesorhizobium loti supplies the vitamin B-{12} required for growth to the freshwater green alga Lobomonas rostrata and where the action of the B-{12} riboswitch is known to be a determinant of system behaviour. Analysis of the model both before and after the add-back of nutrients is carried out. A focus is exploring the robustness of the system. The paper first describes a simple model of algal-bacterial growth and analysis is undertaken. The effect of system parameters and control mechanisms is quantified. Motivated by the inherent switching action within the biology, a sliding mode interpretation of the control mechanisms is hypothesized based on knowledge of the maximum carrying capacities for each growth. The results of a range of experiments reported in the literature are used to validate the assertions.

Type: Proceedings paper
Title: Growth Dynamics of Algal-bacterial Cocultures: A Control Engineering Perspective
Event: 2018 European Control Conference (ECC), 12-15 June 2018, Limassol, Cyprus
ISBN-13: 9783952426982
Open access status: An open access version is available from UCL Discovery
DOI: 10.23919/ECC.2018.8550593
Publisher version: https://doi.org/10.23919/ECC.2018.8550593
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Microorganisms , Algae , Mathematical model , Switches , Biological system modeling , Carbon
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: http://discovery.ucl.ac.uk/id/eprint/10067404
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