Maya Ignatova

Adaptive control of the Simultaneous Saccharification—Fermentation Process from Starch to Ethanol

Abstract In this paper, a new adaptive control strategy for the fed-batch Simultaneous Saccharification—Fermentation Process from Starch to Ethanol (SSFSE) process is proposed in order to maintain the glucose concentration at a quasi-equilibrium state by feeding starch into the process only when the glucose production rate is lower than its consumption rate. By maintaining the equilibrium state for the glucose, it is possible to reach higher values for the ethanol production rate for a longer time; and therefore to increase the ethanol concentration along the process. As the adaptive controller requires online information about the glucose production and consumption rates, software sensors for them are developed. The difference between the estimated values for the consumption and production rates is considered as a control marker, which is used for determining the feeding profile of starch into the fermentor.

REACTION RATE ESTIMATORS OF FED-BATCH PROCESS FOR POLY-β- HYDROXYBUTYRATE (PHB) PRODUCTION BY MIXED CULTURE

ABSTRACT Two estimators of glucose and lactate consumption rates for a fed-batch process of the biodegradable polymer poly-β-hydroxybutyrate (PHB) production by mixed culture of Lactobacillus delbrulckii and Ralstonia eutropha are synthesized. For this purpose, a model for control is derived. Process reaction scheme is proposed on the basis of experimental data and biochemical model of the process. Dynamical equations of the main process variables are derived applying General Dynamical Model Approach. Parameter identification of the model for control is realized using an optimization procedure in MATLAB environment. Verification of the model for control is done. The glucose and lactate consumption rates are estimated by means of observer-based estimators. Their design parameters are calculated using optimal tuning procedure. Estimation results are verified by simulations. Applications of the proposed estimators are discussed.

CONTROL OF ONE STAGE BIO ETHANOL PRODUCTION BY RECOMBINANT STRAIN

ABSTRACT A new method for adaptive control of simultaneous saccharification and fermentation of starch to ethanol by the recombinant strain Saccharomyces cerevisiae YPB—G is proposed. The process monitoring is enriched by new software sensors of glucose consumption and production rates. The difference between their values is defined as a control marker which is used for switching from batch to fed-batch mode automatically and for determining the amplitude and duration of starch feeding pulses (control input). Simulation results have shown that the proposed control strategy stabilizes the process at an equilibrium state for the glucose concentration. In this way, the ethanol concentration in the reactor and the productivity of the process are increased.

Software sensor design considering oscillating conditions as present in industrial scale fed-batch cultivations†

Investigations of inhomogeneous dynamics in industrial‐scale bioreactors can be realized in laboratory simulators. Such studies will be improved by on line observation of the growth of microorganisms and their product synthesis at oscillating substrate availability which represents the conditions in industrial‐scale fed‐batch cultivations. A method for the kinetic monitoring of such processes, supported by on line measurements accessible in industrial practice, is proposed. It consists of a software sensor (SS) system composed of a cascade structure. Process kinetics are simulated in models with a structure including time‐varying yield coefficients. SSs for measured variable kinetics have classical structures. The SS design of unmeasured variables is realized after a linear transformation using a logarithmic function. For these software sensors, a tuning procedure is proposed, at which an arbitrary choice of one tuning parameter value that guarantees stability of the monitoring system allows the calculation of the optimal values of six parameters. The effectiveness of the proposed monitoring approach is demonstrated with experimental data from a glucose‐limited fed‐batch process of Bacillus subtilis in a laboratory two‐compartment scale down reactor which tries to mimic the conditions present in industrial scale nutrient‐limited fed‐batch cultivations. Biotechnol. Bioeng. 2013; 110: 1945–1955.

Modeling Of Oxygen Effect On Kinetics Of Batch Fermentation Process For Yogurt Starter Culture Formation

The aim of this work is to describe the kinetics of yogurt starter culture production by S.thermophilus 13 and Lb. bulgaricus 2-11 and to quantitatively analyse the effect of different dissolved oxygen concentration in the milk on the process trend. Five different mathematical models for description of process kinetics are tested and the best one is selected. The increase of initial concentration of dissolved oxygen leads to a proportional decrease in the specific growth rate of the population and of the rates of lactose consumption and lactic acid production. On the basis of this investigations, two zones of initial dissolved oxygen concentration are defined. In each of these zones, the associated pair of microorganisms have different behaviour.

State Reconstruction in Spatially Distributed BioProcess Systems using Reduced Order Models: Application to the Gluconic Acid Production.

In this work, the dissipative nature of spatially distributed bioprocess systems is exploited to develop efficient state observers based on a low dimensional dynamic representation of the original set of partial differential equations. The approach we suggest combines standard observer design techniques for bioreactors with efficient model reduction methodologies based on projection of the original concentration fields on low dimensional subspaces capturing the slow dynamics of the process. Aspects related with the location of sensors and their influence on the ability to reconstruct concentration fields will also be considered. Finally, the different aspects of the methodology, as well as the efficiency of the resulting observers will be illustrated on a case study of industrial interest, namely a tubular bioreactor producing gluconic acid by Aspergillus Niger.