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Enzymatic synthesis of ampicillin: nonlinear modeling, kinetics estimation, and adaptive control.

Roman M, Selişteanu D - J. Biomed. Biotechnol. (2012)

Bottom Line: First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology.Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process.Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.

View Article: PubMed Central - PubMed

Affiliation: Department of Automatic Control, University of Craiova, A.I. Cuza no. 13, Craiova 200585, Romania.

ABSTRACT
Nowadays, the use of advanced control strategies in biotechnology is quite low. A main reason is the lack of quality of the data, and the fact that more sophisticated control strategies must be based on a model of the dynamics of bioprocesses. The nonlinearity of the bioprocesses and the absence of cheap and reliable instrumentation require an enhanced modeling effort and identification strategies for the kinetics. The present work approaches modeling and control strategies for the enzymatic synthesis of ampicillin that is carried out inside a fed-batch bioreactor. First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology. Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process. Third, by combining an exact linearizing control law with the on-line estimation kinetics algorithm, a nonlinear adaptive control law is designed. The case study discussed shows that a nonlinear feedback control strategy applied to the ampicillin synthesis bioprocess can cope with disturbances, noisy measurements, and parametric uncertainties. Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.

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Bond graph model of the enzymatic synthesis of ampicillin. The directions of half arrows correspond to the run of the reaction, from the reactants towards the reaction products. The mass balances are represented by five 0-junctions, and the mass flows of entering/exiting components are modeled using modulated source flows Sf. The reaction rates are modeled by three modulated two port R elements, MR1, MR2, and MR3. In order to simplify the model representation, the feed flow and the volume are not shown. The bond graph model was depicted in 20 sim environment.
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fig3: Bond graph model of the enzymatic synthesis of ampicillin. The directions of half arrows correspond to the run of the reaction, from the reactants towards the reaction products. The mass balances are represented by five 0-junctions, and the mass flows of entering/exiting components are modeled using modulated source flows Sf. The reaction rates are modeled by three modulated two port R elements, MR1, MR2, and MR3. In order to simplify the model representation, the feed flow and the volume are not shown. The bond graph model was depicted in 20 sim environment.

Mentions: In the above reactions, S1, S2, P1, P2, and P3 represent 6-aminopenicillanic acid (6-APA), phenylglycine methyl ester (PGME), phenylglycine (PG), ampicillin (AMP), and methanol, respectively. φ1, φ2, and φ3 represent the reaction rates of these three reactions, and ki are yield coefficients. Considering that the bioprocess takes place inside a fed-batch bioreactor, from the reaction scheme (6)–(8), and by using the bond graph elements and modeling rules, a bond graph model of the process is obtained see Figure 3.


Enzymatic synthesis of ampicillin: nonlinear modeling, kinetics estimation, and adaptive control.

Roman M, Selişteanu D - J. Biomed. Biotechnol. (2012)

Bond graph model of the enzymatic synthesis of ampicillin. The directions of half arrows correspond to the run of the reaction, from the reactants towards the reaction products. The mass balances are represented by five 0-junctions, and the mass flows of entering/exiting components are modeled using modulated source flows Sf. The reaction rates are modeled by three modulated two port R elements, MR1, MR2, and MR3. In order to simplify the model representation, the feed flow and the volume are not shown. The bond graph model was depicted in 20 sim environment.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3306788&req=5

fig3: Bond graph model of the enzymatic synthesis of ampicillin. The directions of half arrows correspond to the run of the reaction, from the reactants towards the reaction products. The mass balances are represented by five 0-junctions, and the mass flows of entering/exiting components are modeled using modulated source flows Sf. The reaction rates are modeled by three modulated two port R elements, MR1, MR2, and MR3. In order to simplify the model representation, the feed flow and the volume are not shown. The bond graph model was depicted in 20 sim environment.
Mentions: In the above reactions, S1, S2, P1, P2, and P3 represent 6-aminopenicillanic acid (6-APA), phenylglycine methyl ester (PGME), phenylglycine (PG), ampicillin (AMP), and methanol, respectively. φ1, φ2, and φ3 represent the reaction rates of these three reactions, and ki are yield coefficients. Considering that the bioprocess takes place inside a fed-batch bioreactor, from the reaction scheme (6)–(8), and by using the bond graph elements and modeling rules, a bond graph model of the process is obtained see Figure 3.

Bottom Line: First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology.Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process.Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.

View Article: PubMed Central - PubMed

Affiliation: Department of Automatic Control, University of Craiova, A.I. Cuza no. 13, Craiova 200585, Romania.

ABSTRACT
Nowadays, the use of advanced control strategies in biotechnology is quite low. A main reason is the lack of quality of the data, and the fact that more sophisticated control strategies must be based on a model of the dynamics of bioprocesses. The nonlinearity of the bioprocesses and the absence of cheap and reliable instrumentation require an enhanced modeling effort and identification strategies for the kinetics. The present work approaches modeling and control strategies for the enzymatic synthesis of ampicillin that is carried out inside a fed-batch bioreactor. First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology. Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process. Third, by combining an exact linearizing control law with the on-line estimation kinetics algorithm, a nonlinear adaptive control law is designed. The case study discussed shows that a nonlinear feedback control strategy applied to the ampicillin synthesis bioprocess can cope with disturbances, noisy measurements, and parametric uncertainties. Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.

Show MeSH
Related in: MedlinePlus