Dinâmica, otimização e controle de processos de fermentação em estado sólido : desenvolvimento de metodologias em escala laboratorial
Resumo
Solid-state fermentation is characterized by the growth of microorganisms in absence of free
water. In one hand, it is advantageous because simulates their natural environment, enabling
the use of agro industrial residues in natura. On the other hand, it limits heat transfer between
elements, restricting control over the temperature of the medium. In fact, the microbial growth
and the product formation dynamics are directly affected by the environmental conditions and
variations can be harmful to the process productivity. As a consequence, the temperature
increase caused by metabolic heat needs to be avoided. Studies concerning the microbial
dynamics dealing with these variations are scarce. Moreover, it was not found any control laws,
with guarantee of stability, which was designed for a reference tracking and to minimize the
disturbances effects. Thus, two fronts need to be addressed for the solid-state fermentation
viability: the development of a mathematical model able to estimate the effects of
environmental changes in the process; and a temperature control system able to handle the heat
from microbial metabolism. The model was used in a computational algorithm in order to
determine if there was a temperature profile that would be more favorable to the products
formation. In this work two control laws were studied, a proportional integrative, because it is
the most widespread in the industry, and a model base predictive controller, because of its
multivariable control versatility. Both control laws were simulated and then implemented in an
eleven liters agitated drum bioreactor. Some of the various methods for PI controller parameters
settings had their performance and relative stability requirement evaluated. The one that was
proved stable was implemented in the bioreactor. Due to the uncertainties of the fermentation
process, a self-adjustment mechanism was added to the predictive controller, in spite of the
developed mathematical model, in order to avoid some estimation mistakes caused by some
non-estimated states of the real process. The controller achieved an adequate performance with
this approach. The results showed that the microorganisms were more efficient at a constant
32°C temperature. In addition, both developed controllers presented appropriate results facing
the fermentation process requirement, with mean deviances from the referential temperature
below 0,6°C and a maximum error of 2,8°C.
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