INVESTIGADORES
GARELLI fabricio
congresos y reuniones científicas
Título:
Control of overflow metabolism via sliding mode reference conditioning
Autor/es:
JESÚS PICO; FABRICIO GARELLI; HERNÁN DE BATTISTA
Lugar:
Seúl, Corea.
Reunión:
Congreso; 17th IFAC World Congress (International Federation of Automatic Control); 2008
Institución organizadora:
International Federation of Automatic Control
Resumen:
In many biotechnological processes, the optimal productivity corresponds to operating at critical substrate concentration. The problem, then, consists of maximizing the feeding rate compatible with the critical constraint, so as to avoid overflow metabolism. This value may be unknown and may change from experiment to experiment and from strain to strain, and even in the same experiment due to changing environmental and/or process conditions. In previous works different strategies to cope with this problem have been applied to microorganisms of industrial interest, such as E. coli and S. cerevisiae. Thus, probing strategies have been used in fedbatch bioreactors to operate close to their maximum oxygen transfer rate while avoiding acetate accumulation in the first case. In the fed-batch fermentation of S. cerevisiae a small amount of ethanol is allowed to be present in the culture, and the control problem in one of regulating the ethanol concentration a a given low reference value. E. coli and S. cerevisiae. Thus, probing strategies have been used in fedbatch bioreactors to operate close to their maximum oxygen transfer rate while avoiding acetate accumulation in the first case. In the fed-batch fermentation of S. cerevisiae a small amount of ethanol is allowed to be present in the culture, and the control problem in one of regulating the ethanol concentration a a given low reference value. Here an approach based on sliding mode reference conditioning is proposed to drive the system to a maximum specific growth rate compatible with a given constraint (e.g. ethanol concentration lower than a given threshold). It is shown how this approach is robust with respect to uncertainties in the process dynamics and with respect to unknown perturbations affecting the critical point.
