Vol. 23, No. 3 (2024), Sim24296 https://doi.org/10.24275/rmiq/Sim24296


Adaptive sliding mode control of a bioreactor via nutrients variable control using a diffeomorphism


 

Authors

A.E. Rodriguez-Mata, J.A. Medrano-Hermosillo, V.A. Gonzalez-Huitron, L. Djilali, P.A. Lopez-Perez, A. Sonck


Abstract

Bioengineering has advanced thanks to progress in chemical engineering and control theory, leading to the development and production of innovative drugs and medical treatments. Our research introduces a new and reliable adaptive sliding mode control (ASMC) method that involves an initial mixing phase of the substrate before injecting it into the bioreactor, focusing on regulating nutrient concentrations. By using a diffeomorphism, we break down mathematical properties like bilinearity, enabling us to create a a chain-like structure system to implement nonlinear ASMC effectively. This fresh approach shows promise in enhancing the efficiency and output of fermentation processes, opening up new possibilities for controlling biomass production in the fermentation industry.


Keywords

Bioreactor, adaptive sliding modes, nutrient concentration control, bilinearity elimination.


References

  • Aguilar, R., Soto, G., Martínez, S., & Yescas, R. M. (2004). Substrate regulation in fixed bed bioreactors via feedback control. Revista Mexicana de Ingeniería Química, 3(1), 1-11.
  • Aguilar-Ibanez, C., Saldivar, B., Lizarraga, M. J., Garcia-Canseco, E., and Garrido, R. (2021). Parametric uncertain second-order linear system output-adaptive stabilization: An integral and mrca based approach. European Journal of Control, 57:76–81. https://doi.org/10.1016/j.ejcon.2020.04.002
  • Aguilar-López, R., López-Pérez, P. A., Neria-González, M. I., & Domínguez-Bocanegra, A. R. (2010). Modelo adaptable basado en un observador para una clase de bio-reactor aerobio por lotes. Revista mexicana de ingeniería química, 9(1), 29-35.
  • Aguilar-López, R., Soto-Cortés, G., & Neria-González, M. I. (2006). Monitoreo en linea de un bioreactor continuo empleando observadores de modo deslizante. Revista Mexicana de Ingeniería Química, 5(1), 1-4.
  • Alvarez-Ramirez, J., Meraz, M., and Jaime Vernon-Carter, E. (2019). A theoretical derivation of the monod equation with a kinetics sense. Biochemical Engineering Journal, 150:107305. https://doi.org/10.1016/j.bej.2019.107305
  • Celikovsky, S., Torres-Munoz, J., Rodriguez-Mata, A., and Dominguez-Bocanegra, A. R. (2015). An adaptive extension to high gain observer with application to wastewater monitoring. In 2015 12th international conference on electrical engineering, computing science and automatic control (cce), pages 1–6. IEEE.
  • Chao, R., Mishra, S., Si, T., and Zhao, H. (2017). Engineering biological systems using automated biofoundries. Metabolic Engineering, 42:98–108. https://doi.org/10.1016/j.ymben.2017.06.003
  • de Souza, A. R., Gouzé, J.-L., Efimov, D., and Polyakov, A. (2020). Robust adaptive stimation in the competitive chemostat. Computers & Chemical Engineering, 142:107030. https://doi.org/10.1016/j.compchemeng.2020.107030
  • Ekpenyong, M., Asitok, A., Antigha, R., Ogarekpe, N., Ekong, U., Asuquo, M., Essien, J., and Antai, S. (2021). Bioprocess optimization of nutritional parameters for enhanced anti-leukemic l-asparaginase production by aspergillus candidus uccm 00117: a sequential statistical approach. International Journal of Peptide Researc and Therapeutics, 27(2):1501–1527. https://doi.org/10.1007/s10989-021-10188-x
  • Estrada, J. S. and Camacho, O. (2021). Adaptive Sliding Mode Control for a pH Neutralization Reactor: An approach based on Takagi-Sugeno Fuzzy Multimodel. In 2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM). IEEE.
  • Garza, D. R., Gonze, D., Zafeiropoulos, H., Liu, B., and Faust, K. (2023). Metabolic models of human gut microbiota: Advances and challenges. Cell Systems, 14(2):109–121. https://doi.org/10.1016/j.cels.2022.11.002
  • Gorin, G., & Pachter, L. (2022). Distinguishing biophysical stochasticity from technical noise in single-cell RNA sequencing using Monod. bioRxiv, 2022-06. https://doi.org/10.1101/2022.06.11.495771
  • Haidar, I., Desmond-Le Quéméner, E., Barbot, J.-P., Harmand, J., and Rapaport, A. (2022). Modeling and Optimal Control of an Electro-Fermentation Process within a Batch Culture. Processes, 10(3):535. https://doi.org/10.3390/pr10030535
  • Hartmann, F. S., Udugama, I. A., Seibold, G. M., Sugiyama, H., and Gernaey, K. V. (2022). Digital models in biotechnology: Towards multi-scale integration and implementation. Biotechnology Advances, page 108015. https://doi.org/10.1016/j.biotechadv.2022.108015
  • Jin, Z., Ng, A., Maurice, C. F., & Juncker, D. (2022). The Mini Colon Model: a benchtop multi-bioreactor system to investigate the gut microbiome. Gut Microbes, 14(1), 2096993. https://doi.org/10.1080/19490976.2022.2096993
  • Kesik‐Brodacka, M. (2018). Progress in biopharmaceutical development. Biotechnology and applied biochemistry, 65(3), 306-322. https://doi.org/10.1002/bab.1617
  • Linets, G., Bazhenov, A., Melnikov, S., Grivennaya, N., & Malygin, S. (2023, January). Development of a mathematical model for assessing the state of plant biomass using the integration of multispectral sensors of optical and radio ranges. In 2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022) (Vol. 12564, pp. 93-99). SPIE. https://doi.org/10.1117/12.2669450
  • Lisci, S., Grosso, M., and Tronci, S. (2021). Different control strategies for a yeast fermentation bioreactor. IFACPapersOnLine, 54(3):306–311. https://doi.org/10.1016/j.ifacol.2021.08.259
  • López, R. A., Pérez, P. A. L., and Femat, R. (2020). Control in Bioprocessing: Modeling, Estimation and the Use of Soft Sensors. John Wiley & Sons. USA
  • Lopéz-Peréz, P. A., Rodriguez-Mata, A. E., Hernández-González, O., Amabilis-Sosa, L. E., Baray-Arana, R., and Leon-Borges, J. (2022a). Design of a Robust sliding mode controller for bioreactor cultures in overflow metabolism via an interdisciplinary approach. Open Chemistry, 20(1):120–129. https://doi.org/10.1515/chem-2021-0098
  • Mitra, S. and Murthy, G. S. (2021). Bioreactor control systems in the biopharmaceutical industry: a critical perspective. Systems Microbiology and Biomanufacturing, 2(1):91–112. https://doi.org/10.1007/s43393-021-00048-6
  • Morales-Díaz, A., & Carlos-Hernández, S. (2010). Diseño de un control saturado para la regulación de sustrato en un bioreactor anaeróbico continuo. Revista mexicana de ingeniería química, 9(2), 219-229.
  • Pajčin, I., Knežić, T., Savic Azoulay, I., Vlajkov, V., Djisalov, M., Janjušević, L., ... & Gadjanski, I. (2022). Bioengineering outlook on cultivated meat production. Micromachines, 13(3), 402. https://doi.org/10.3390/mi13030402
  • Picó-Marco, E., Picó*, J., and De Battista, H. (2005). Sliding mode scheme for adaptive specific growth rate control in biotechnological fed-batch processes. International Journal of Control, 78(2):128–141. https://doi.org/10.1080/002071705000073772
  • Prasad, D., Kumar, M., Srivastav, A., and Singh, R. S. (2019). Modeling of Multiple Steady-state Behavior and Control of a Continuous Bioreactor. Indian Journal of Science and Technology, 12(11):1–12. https://dx.doi.org/10.17485/ijst/2019/v12i11/140476
  • Rathore, A. S., Mishra, S., Nikita, S., & Priyanka, P. (2021). Bioprocess control: current progress and future perspectives. Life, 11(6), 557.Bourriot, S., Garnier, C. and Doublier, J.L. (1999). Phase separation, rheology and microstructure of micellar casein-guar gum mixtures. Food Hydrocolloids 7, 90-95. https://doi.org/10.1016/S0268-005X(98)00068-X 
  • Rayane K., Bougrine M., Abu-Rub H., Benalia A. and Trabelsi M. (2023). Average Model-Based Sliding Mode Control for Quality Improvement of a Grid-Connected PUC Inverter, in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 11, no. 4, pp. 3765-3774, Aug. 2023, doi: 10.1109/JESTPE.2023.3264856.
  • Ritonja, J., Goršek, A., and Pecar, D. (2020). Use of a Heating System to Control the Probiotic Beverage Production in Batch Bioreactor. Applied Sciences, 11(1):84. https://doi.org/10.3390/app11010084
  • Robles-Magdaleno, J., Rodríguez-Mata, A., Farza, M., and M’saad, M. (2020). A filtered high gain observer for a class of non uniformly observable systems–application to a phytoplanktonic growth model. Journal of Process Control, 87:68–78. https://doi.org/10.1016/j.jprocont.2020.01.007
  • Rodríguez-Mariano, A., Reynoso-Meza, G., Páramo-Calderón, D. E., Chávez-Conde, E., García-Alvarado, M. A., & Carrillo-Ahumada, J. (2015). Análisis del desempenño de controladores lineales sintonizados en diferentes estados estacionarios del biorreactor de cholette mediante técnicas de decisión multi-criterio. Revista mexicana de ingeniería química, 14(1), 167-204.
  • Rodríguez-Mata, A. E., Luna, R., Pérez-Correa, J. R., Gonzalez-Huitrón, A., Castro-Linares, R., and DuarteMermoud, M. A. (2020). Fractional sliding mode nonlinear procedure for robust control of an eutrophying microalgae photobioreactor. Algorithms, 13(3):50. https://doi.org/10.3390/a13030050
  • Seli¸steanu, D., Petre, E., and R asvan, V. B. (2007). Sliding mode and adaptive sliding-mode control of a class of nonlinear bioprocesses. International Journal of Adaptive Control and Signal Processing, 21(8-9):795–822. https://doi.org/10.1002/acs.973
  • Shariatzadeh, M., Lopes, A. G., Glen, K. E., Sinclair, A., and Thomas, R. J. (2021) Application of a simple unstructured kinetic and cost of goods models to support t-cell therapy manufacture. Biotechnology Progress,37(6), e3205. https://doi.org/10.1002/btpr.3205
  • Sudha, R., Shunmugathammal, M., Vijayalakshmi, S., Radhakrishnan, G., D, H., and Rani, S. S. (2021). Design of Temperature Control in Solid State Fermentation Process for the Production of Enzyme. In 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE.
  • Tomic, O., Forde, C., Delahunty, C., & Næs, T. (2013). Performance indices in descriptive sensory analysis–A complimentary screening tool for assessor and panel performance. Food Quality and Preference, 28(1), 122-133. https://doi.org/10.1016/j.foodqual.2012.06.012
  • Vásquez, M., Yanascual, J., Herrera, M., Prado, A., and Camacho, O. (2023). A hybrid sliding mode control based on a nonlinear pid surface for nonlinear chemical processes. Engineering Science and Technology, an International Journal, 40:101361. https://doi.org/10.1016/j.jestch.2023.101361
  • Yabo, A. G., Caillau, J.-B., and Gouzé, J.-L. (2020). Optimal bacterial resource allocation: metabolite production in continuous bioreactors. Mathematical Biosciences and Engineering, 17(6):7074–7100. https://doi.org/10.3934/mbe.2020364
  • Zlateva, P. (2020). A modified sliding mode control of a nonlinear methane fermentation process. In E3S Web of Conferences (Vol. 167, p. 05007). EDP Sciences. https://doi.org/10.1051/e3sconf/202016705007