e-journal
On-line yeast propagation process monitoring and control using an intelligent automatic control system
The monitoring and control of bioprocesses is a challenging task. This applies particularly
if the actions to the process have to be carried out in real-time. This work
presents a systemfor on-linemonitoring and control of batch yeast propagation under
limiting conditions based on a virtual plant operator, which uses the concept of
intelligent control algorithms by means of fuzzy logic theory. Process information is
provided on-line using a sensor array comprising themeasurement ofOD, operating
temperature, pressure, density, dissolved oxygen, and pH value. In this context practical
problems arising through on-line sensing and signal processing are addressed.
The preprocessed sensor data are fed to a neural network for on-line biomass estimation.
The root mean squared error of prediction is 4 × 106 cells/mL. The proposed
system then triggers temperature and aeration by usage of a temperature dependent
metabolic growth model and sensor data. The deviation of the predicted biomass
from that of the reference trajectory as modeled by the metabolic growth model and
its temporal derivative are used as inputs for the fuzzy temperature controller. The
inputs used by the fuzzy aeration controller are the deviation of measured extract
from that of the reference trajectory, the predicted cell count, and the dissolved
oxygen concentration. The fuzzy-based expert system allows to provide the desired
yeast cell concentration of 100–120 × 106 cells/mL at a minimum residual extract
limit of 6.0 g/100 g at the required point of time. Thus, a dynamic adjustment of
the propagation process to the overall production schedule is possible in order to
produce the required amount of biomass at the right time.
Keywords: Expert system / Fuzzy logic control / Intelligent control / On-line monitoring / Yeast
propagation
Tidak ada salinan data
Tidak tersedia versi lain