Digital Library of the European Council for Modelling and Simulation

Title:	An Embedded System Implementation Of A Predictive Algorithm For A Bioprocess
Authors:	Florin Stinga, Marius Marian, Valentin Kese, Lucian Barbulescu, Emil Petre
Published in:	(2017).ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi:10.7148/2017 ISBN: 978-0-9932440-4-9/ ISBN: 978-0-9932440-5-6 (CD) 31st European Conference on Modelling and Simulation, Budapest, Hungary, May 23^rd – May 26^th, 2017
Citation format:	Florin Stinga, Marius Marian, Valentin Kese, Lucian Barbulescu, Emil Petre (2017). An Embedded System Implementation Of A Predictive Algorithm For A Bioprocess, ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi: 10.7148/2017-0409
DOI:	https://doi.org/10.7148/2017-0409
Abstract:	The modeling and control of biotechnological processes is an actual and challenging problem due to their complicated structure. It is well known that these processes are dealing with living organisms that evolve over a long time or at the smallest change in their environment can become highly sensitive. Therefore, the bioprocesses are characterized by highly nonlinear and uncertain dynamics, and their mathematical model is complex (G. Bastin and D. Dochain 1990; O. Bernard et al. 2011; F. Mairet et al. 2011). One of these processes whose importance resides in strict environmental rules is the wastewater treatment process; these rules are imposed in order to limit the quantity of toxic matter released in industrial and urban effluents. Nevertheless, its main drawback is the production of carbon dioxide (CO2) and its easy destabilization to input variations. For CO2 mitigation, a solution consist in the growth of some microalgae populations that by using light as source of energy are able to assimilate inorganic forms of carbon and to convert them into requisite organic substances for cellular functions, generating at the same time oxygen (O2). In what concerns the control of these processes, during the last years, numerous control strategies were developed: linearizing feedback (I. Neria-González et al 2009), adaptive and robust-adaptive (D. Selisteanu et al. 2007), predictive control (S. Tebbani et al. 2014), so on. Moreover, the widespread use of the embedded systems, based on microcontrollers, offered the hardware support for testing and implementing such complex control algorithms.
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