Optimized Dissolved Oxygen Fuzzy Control for Recombinant Escherichia coli Cultivations
| Autor: | Antonio Carlos Luperni Horta, Rafael Akira Akisue, Ruy de Sousa Junior, Matheus Lopes Harth |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Numerical Analysis
Industrial engineering. Management engineering Fuzzy set Decision tree fuzzy control Fuzzy control system QA75.5-76.95 recombinant Escherichia coli T55.4-60.8 Fuzzy logic Flow measurement Theoretical Computer Science Computational Mathematics SUPERSYS_HCDC Computational Theory and Mathematics Control theory dissolved oxygen Electronic computers. Computer science adaptive network-based fuzzy inference system Bioreactor Biological system Membership function Mathematics |
| Zdroj: | Algorithms, Vol 14, Iss 326, p 326 (2021) Algorithms Volume 14 Issue 11 |
| ISSN: | 1999-4893 |
| Popis: | Due to low oxygen solubility and mechanical stirring limitations of a bioreactor, ensuring an adequate oxygen supply during a recombinant Escherichia coli cultivation is a major challenge in process control. Under the light of this fact, a fuzzy dissolved oxygen controller was developed, taking into account a decision tree algorithm presented in the literature, and implemented in the supervision software SUPERSYS_HCDC. The algorithm was coded in MATLAB with its membership function parameters determined using an Adaptive Network-Based Fuzzy Inference System tool. The controller was composed of three independent fuzzy inference systems: Princ1 and Princ2 assessed whether there would be an increment or a reduction in air and oxygen flow rates (respectively), whilst Delta estimated the size of these variations. To test the controller, simulations with a neural network model and E. coli cultivations were conducted. The fuzzification of the decision tree was successful, resulting in smoothing of air and oxygen flow rates and, hence, in an attenuation of dissolved oxygen oscillations. Statistically, the average standard deviation of the fuzzy controller was 2.45 times lower than the decision tree (9.48%). Results point toward an increase in the flow meter lifespan and a possible reduction of the metabolic stress suffered by E. coli during the cultivation. |
| Databáze: | OpenAIRE |
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