Hybrid Control Scheme for Anaerobic Digestion in a CSTR-UASB Reactor System
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Published:
Jul 21, 2020
Keywords:
CSTR-UASB reactors Input-output linearization control Wastewater treatment Coupled PDEODE system Anaerobic digestion
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Abstract
Anaerobic digestion is an important wastewater treatment technology for industrial wastewater. To achieve the target of global environmental regulation, process control plays an important role in the system operation. The control system for anaerobic digestion process is generally applied to each reactor separately without consideration of variables that mutually affect the operation of the other one. This work proposes a hybrid control scheme for a CSTR-UASB reactor system described by a PDE-ODE model. The CSTR system is employed to rapidly reduce the inlet COD concentration while the UASB reactor is used to accurately regulate the outlet COD concentration of the system. An input-output (I/O) linearization and proportional-integral (PI) control techniques are applied to formulate the control scheme for the process. The distributed variables are applied to the developed control system for handling the spatially distributed dynamics of the bacterial biomass. The COD concentration of both reactors are manipulated through the dilution rate and feed flow rate to achieve the desired targets. Simulation results of the closed-loop system illustrate that the developed control scheme regulates the controlled outputs to follow the desired trajectories and manipulate the control problems effectively.
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Tawai, A., Kitsubthawee, K., Panjapornpon, C., & Shao, W. (2020). Hybrid Control Scheme for Anaerobic Digestion in a CSTR-UASB Reactor System. Applied Science and Engineering Progress, 13(3), 213–223. Retrieved from https://ph02.tci-thaijo.org/index.php/ijast/article/view/241541
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References
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[21] A. Sophan and C. Thongchaisuratkrul, “An enhancement of lighting system energy efficiency using an automatic light dimming control,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 2, pp. 93–101, 2018.
[22] K. C. Draa, H. Voos, M. Alma, A. Zemouche, and M. Darouach, “An LMI-Based H∞ discrete-time nonlinear state observer design for an anaerobic digestion model,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 11547–11552, 2017.
[23] S. Sriprang, B. Nahid-Mobarakeh, N. Takorabet, S. Pierfederici, N. Bizon, P. Kuman, and P. Thounthong, “Permanent magnet synchronous motor dynamic modeling with state observer-based parameter estimation for AC servomotor drive application,” Applied Science and Engineering Progress, vol. 12, no. 4, pp. 286–297, 2019.
[24] D. Chuenbubpar, T. R. Srinophakhun, and P. Tohsakul, “Plant-wide process simulation of ethanol production from empty fruit bunch,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 1, pp. 53–61, 2018.
[25] W. Songserm, T. Wuttipornpun, and C. Jaturanonda, “Hybrid metaheuristics and linear programming for finite capacity MRP in multi-stage flexible flow shop with permutation and non-permutation scheduling options,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 3, pp. 173–183, 2018.
[26] P. O. Yeesa, P. Srisuradetchai, and J. J. Borkowski, “Model-robust G-optimal designs in the presence of block effects,” Applied Science and Engineering Progress, vol. 12, no. 3, pp. 198–208, 2019.
[27] F. Farida, N. Makaje, and A. Phon-On, “A simplified approach to estimating parameter of the GARCH (1, 1) Model,” Applied Science and Engineering Progress, vol. 12, no. 3, pp. 158–163, 2019.
[2] E. Foresti, M. Zaiat, and M. Vallero, “Anaerobic processes as the core technology for sustainable domestic wastewater treatment: Consolidated applications, new trends, perspectives, and challenges,” Reviews in Environmental Science and Bio/Technology, vol. 5, no. 1, pp. 3–19, 2006.
[3] H. O. Méndez-Acosta, B. Palacios-Ruiz, V. Alcaraz-González, V. González-Álvarez, and J. P. García- Sandoval, “A robust control scheme to improve the stability of anaerobic digestion processes,” Journal of Process Control, vol. 20, no. 4, pp. 375– 383, 2010.
[4] F. I. Turkdogan-Aydınol and K. Yetilmezsoy, “A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater,” Journal of Hazardous Materials, vol. 182, no.1–3, pp. 460–471, 2010.
[5] S. Mahachaichanakul and P. Srisuradetchai, “Applying the median and genetic algorithm to construct D-and G-optimal robust designs against missing data,” Applied Science and Engineering Progress, vol. 12, no. 1, pp. 3–13, 2019.
[6] C. Waewsak, A. Nopharatana, and P. Chaiprasert, “Neural-fuzzy control system application for monitoring process response and control of anaerobic hybrid reactor in wastewater treatment and biogas production,” Journal of Environmental Sciences, vol.22, no. 12, pp. 1883–1890, 2010.
[7] S. Mu, Y. Zeng, and P. Wu, “Multivariable control of anaerobic reactor by using external recirculation and bypass ratio,” Journal of Chemical Technology and Biotechnology, vol. 83, no. 6, pp. 892–903, 2008.
[8] W. J. Liu and M. Krstić, “Backstepping boundary control of Burgers’ equation with actuator dynamics,” Systems & Control Letters, vol. 41, no. 4, pp. 291–303, 2000.
[9] A. Tawai and C. Panjapornpon, “Input–output linearizing control strategy for an ethylene dichloride cracking furnace using a coupled PDE-ODE model,” Industrial & Engineering Chemistry Research, vol. 55, no. 3, pp. 683–691, 2006.
[10] A. Tawai, C. Panjapornpon, M. Sriariyanun, and K. Cheenkachorn, “Control of anaerobic digestion reactor with recirculation using an Input-output linearizing control strategy,” IFACPapersOnLine, vol. 51, no. 28, pp. 109–114, 2018.
[11] F. J. Benitez, J. Beltran‐Heredia, F. J. Real, and T. Gonzalez, “Aerobic and anaerobic purification of wine distillery wastewater in batch reactors,” Chemical Engineering & Technology: Industrial Chemistry ‐ Plant Equipment ‐ Process Engineering ‐ Biotechnology, vol. 22, no. 2, pp. 165–172, 1999.
[12] R. Borja, A. Martin, M. Luque, and M. M. Duran, “Kinetic study of anaerobic digestion of wine distillery wastewater,” Process Biochemistry, vol. 28, no. 2, pp. 83–90, 1993.
[13] R. Borja, A. Martin, R. Maestro, M. Luque, and M. M. Durán, “Enhancement of the anaerobic digestion of wine distillery wastewater by the removal of phenolic inhibitors,” Bioresource Technology, vol. 45, no. 2, pp. 99–104, 1993.
[14] Y. Zeng, S. J. Mu, S. J. Lou, B. Tartakovsky, S. R. Guiot, and P. Wu, “Hydraulic modeling and axial dispersion analysis of UASB reactor,” Biochemical Engineering Journal, vol. 25, no. 2, pp. 113–123, 2005.
[15] S. J. Mu, Y. Zeng, B. Tartakovsky, and P. Wu, “Simulation and control of an upflow anaerobic sludge blanket (UASB) reactor using an ADM1- based distributed parameter model,” Industrial & Engineering Chemistry Research, vol. 46, no. 5, pp. 1519–1526, 2007.
[16] S. J. Mu, Y. Zeng, P. Wu, S. J. Lou, and B. Tartakovsky, “Anaerobic digestion model no. 1-based distributed parameter model of an anaerobic reactor: I. Model development,” Bioresource Technology, vol. 99, no. 9, pp. 3665–3675, 2008.
[17] O. Bernard, Z. Hadj-Sadok, D. Dochain, A. Genovesi, and J. P. Steyer, “Dynamical model development and parameter identification for an anaerobic wastewater treatment process,” Biotechnology and Bioengineering, vol. 75, no. 4, pp. 424–438, 2001.
[18] M. Sriariyanun, D. H. Q. Anh, P. Tantayotai, and K. Cheenkachorn, “Anammox process: The principle, the technological development and recent industrial applications,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 8, no. 4, pp. 237– 244, 2015.
[19] P. V. Danckwerts, “Continuous flow systems: Distribution of residence times,” Chemical Engineering Science, vol. 2, no. 1, pp. 1–13, 1953.
[20] M. Perrier and D. Dochain, “Evaluation of control strategies for anaerobic digestion processes,” International Journal of Adaptive Control and Signal Processing, vol. 7, no. 4, pp. 309–321, 1993.
[21] A. Sophan and C. Thongchaisuratkrul, “An enhancement of lighting system energy efficiency using an automatic light dimming control,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 2, pp. 93–101, 2018.
[22] K. C. Draa, H. Voos, M. Alma, A. Zemouche, and M. Darouach, “An LMI-Based H∞ discrete-time nonlinear state observer design for an anaerobic digestion model,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 11547–11552, 2017.
[23] S. Sriprang, B. Nahid-Mobarakeh, N. Takorabet, S. Pierfederici, N. Bizon, P. Kuman, and P. Thounthong, “Permanent magnet synchronous motor dynamic modeling with state observer-based parameter estimation for AC servomotor drive application,” Applied Science and Engineering Progress, vol. 12, no. 4, pp. 286–297, 2019.
[24] D. Chuenbubpar, T. R. Srinophakhun, and P. Tohsakul, “Plant-wide process simulation of ethanol production from empty fruit bunch,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 1, pp. 53–61, 2018.
[25] W. Songserm, T. Wuttipornpun, and C. Jaturanonda, “Hybrid metaheuristics and linear programming for finite capacity MRP in multi-stage flexible flow shop with permutation and non-permutation scheduling options,” King Mongkut’s University of Technology North Bangkok International Journal of Applied Science and Technology, vol. 11, no. 3, pp. 173–183, 2018.
[26] P. O. Yeesa, P. Srisuradetchai, and J. J. Borkowski, “Model-robust G-optimal designs in the presence of block effects,” Applied Science and Engineering Progress, vol. 12, no. 3, pp. 198–208, 2019.
[27] F. Farida, N. Makaje, and A. Phon-On, “A simplified approach to estimating parameter of the GARCH (1, 1) Model,” Applied Science and Engineering Progress, vol. 12, no. 3, pp. 158–163, 2019.