Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor

Mohamad Hassan Hamadelnil Deifalla; Gurashi Abdalla Gasmelseed

doi:doi:10.11648/j.ajche.20241206.11

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Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor

Mohamad Hassan Hamadelnil Deifalla^*

, Gurashi Abdalla Gasmelseed

Published in American Journal of Chemical Engineering (Volume 12, Issue 6)

Received: 5 November 2024 Accepted: 20 December 2024 Published: 31 December 2024

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Abstract

Effective temperature control in continuous stirred-tank reactors (CSTRs) is essential for maintaining product quality and process stability in nonlinear chemical systems. Traditional PID controllers, tuned via Ziegler-Nichols (ZN) methods, often struggle to manage the nonlinearities of such systems, leading to high overshoot, prolonged settling times, and suboptimal disturbance rejection. This study introduces a genetic algorithm (GA)-based approach for optimizing PID controller parameters to enhance the performance of temperature control during the saponification of ethyl acetate in a CSTR, a mildly exothermic reaction characterized by second-order kinetics. The proposed method employs the integral of time-weighted absolute error (ITAE) as a fitness function to iteratively minimize system error and optimize controller gains. Comparative analysis with the ZN-tuned PID controller reveals substantial improvements using the GA-tuned PID controller, including a reduction in overshoot from 61.4% to 38.1%, and decreases in rise, peak, and settling times by 29.7%, 35.3%, and 72.02%, respectively. Additionally, the GA-PID controller demonstrates superior set-point tracking and robust disturbance rejection, achieving a system error reduction of 68.1% compared to the ZN-PID controller. These results underscore the efficacy of genetic algorithms in overcoming the limitations of conventional tuning methods for nonlinear systems. The GA-based tuning approach not only enhances control accuracy and stability but also offers a scalable solution for optimizing complex industrial processes, paving the way for advancements in chemical reactor control and broader applications in process engineering.

Published in	American Journal of Chemical Engineering (Volume 12, Issue 6)
DOI	10.11648/j.ajche.20241206.11
Page(s)	123-131
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

PID Controller, CSTR, Ziegler-Nichols, Genetic Algorithm, Tuning, Optimization

References

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APA Style

Deifalla, M. H. H., Gasmelseed, G. A. (2024). Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. American Journal of Chemical Engineering, 12(6), 123-131. https://doi.org/10.11648/j.ajche.20241206.11

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ACS Style

Deifalla, M. H. H.; Gasmelseed, G. A. Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. Am. J. Chem. Eng. 2024, 12(6), 123-131. doi: 10.11648/j.ajche.20241206.11

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AMA Style

Deifalla MHH, Gasmelseed GA. Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. Am J Chem Eng. 2024;12(6):123-131. doi: 10.11648/j.ajche.20241206.11

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@article{10.11648/j.ajche.20241206.11,
  author = {Mohamad Hassan Hamadelnil Deifalla and Gurashi Abdalla Gasmelseed},
  title = {Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor
},
  journal = {American Journal of Chemical Engineering},
  volume = {12},
  number = {6},
  pages = {123-131},
  doi = {10.11648/j.ajche.20241206.11},
  url = {https://doi.org/10.11648/j.ajche.20241206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajche.20241206.11},
  abstract = {Effective temperature control in continuous stirred-tank reactors (CSTRs) is essential for maintaining product quality and process stability in nonlinear chemical systems. Traditional PID controllers, tuned via Ziegler-Nichols (ZN) methods, often struggle to manage the nonlinearities of such systems, leading to high overshoot, prolonged settling times, and suboptimal disturbance rejection. This study introduces a genetic algorithm (GA)-based approach for optimizing PID controller parameters to enhance the performance of temperature control during the saponification of ethyl acetate in a CSTR, a mildly exothermic reaction characterized by second-order kinetics. The proposed method employs the integral of time-weighted absolute error (ITAE) as a fitness function to iteratively minimize system error and optimize controller gains. Comparative analysis with the ZN-tuned PID controller reveals substantial improvements using the GA-tuned PID controller, including a reduction in overshoot from 61.4% to 38.1%, and decreases in rise, peak, and settling times by 29.7%, 35.3%, and 72.02%, respectively. Additionally, the GA-PID controller demonstrates superior set-point tracking and robust disturbance rejection, achieving a system error reduction of 68.1% compared to the ZN-PID controller. These results underscore the efficacy of genetic algorithms in overcoming the limitations of conventional tuning methods for nonlinear systems. The GA-based tuning approach not only enhances control accuracy and stability but also offers a scalable solution for optimizing complex industrial processes, paving the way for advancements in chemical reactor control and broader applications in process engineering.
},
 year = {2024}
}

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TY  - JOUR
T1  - Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor

AU  - Mohamad Hassan Hamadelnil Deifalla
AU  - Gurashi Abdalla Gasmelseed
Y1  - 2024/12/31
PY  - 2024
N1  - https://doi.org/10.11648/j.ajche.20241206.11
DO  - 10.11648/j.ajche.20241206.11
T2  - American Journal of Chemical Engineering
JF  - American Journal of Chemical Engineering
JO  - American Journal of Chemical Engineering
SP  - 123
EP  - 131
PB  - Science Publishing Group
SN  - 2330-8613
UR  - https://doi.org/10.11648/j.ajche.20241206.11
AB  - Effective temperature control in continuous stirred-tank reactors (CSTRs) is essential for maintaining product quality and process stability in nonlinear chemical systems. Traditional PID controllers, tuned via Ziegler-Nichols (ZN) methods, often struggle to manage the nonlinearities of such systems, leading to high overshoot, prolonged settling times, and suboptimal disturbance rejection. This study introduces a genetic algorithm (GA)-based approach for optimizing PID controller parameters to enhance the performance of temperature control during the saponification of ethyl acetate in a CSTR, a mildly exothermic reaction characterized by second-order kinetics. The proposed method employs the integral of time-weighted absolute error (ITAE) as a fitness function to iteratively minimize system error and optimize controller gains. Comparative analysis with the ZN-tuned PID controller reveals substantial improvements using the GA-tuned PID controller, including a reduction in overshoot from 61.4% to 38.1%, and decreases in rise, peak, and settling times by 29.7%, 35.3%, and 72.02%, respectively. Additionally, the GA-PID controller demonstrates superior set-point tracking and robust disturbance rejection, achieving a system error reduction of 68.1% compared to the ZN-PID controller. These results underscore the efficacy of genetic algorithms in overcoming the limitations of conventional tuning methods for nonlinear systems. The GA-based tuning approach not only enhances control accuracy and stability but also offers a scalable solution for optimizing complex industrial processes, paving the way for advancements in chemical reactor control and broader applications in process engineering.

VL  - 12
IS  - 6
ER  -

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Author Information

Mohamad Hassan Hamadelnil Deifalla

Chemical Engineering Department, Sudan University of Science and Technology, Khartoum, Sudan

Contact Email

http://orcid.org/0009-0003-3818-4087
Gurashi Abdalla Gasmelseed

Chemical Engineering Department, University of Science and Technology, Khartoum, Sudan

Contact Email

http://orcid.org/0009-0006-4887-9984

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APA Style

Deifalla, M. H. H., Gasmelseed, G. A. (2024). Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. American Journal of Chemical Engineering, 12(6), 123-131. https://doi.org/10.11648/j.ajche.20241206.11

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ACS Style

Deifalla, M. H. H.; Gasmelseed, G. A. Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. Am. J. Chem. Eng. 2024, 12(6), 123-131. doi: 10.11648/j.ajche.20241206.11

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AMA Style

Deifalla MHH, Gasmelseed GA. Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor. Am J Chem Eng. 2024;12(6):123-131. doi: 10.11648/j.ajche.20241206.11

Copy | Download

@article{10.11648/j.ajche.20241206.11,
  author = {Mohamad Hassan Hamadelnil Deifalla and Gurashi Abdalla Gasmelseed},
  title = {Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor
},
  journal = {American Journal of Chemical Engineering},
  volume = {12},
  number = {6},
  pages = {123-131},
  doi = {10.11648/j.ajche.20241206.11},
  url = {https://doi.org/10.11648/j.ajche.20241206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajche.20241206.11},
  abstract = {Effective temperature control in continuous stirred-tank reactors (CSTRs) is essential for maintaining product quality and process stability in nonlinear chemical systems. Traditional PID controllers, tuned via Ziegler-Nichols (ZN) methods, often struggle to manage the nonlinearities of such systems, leading to high overshoot, prolonged settling times, and suboptimal disturbance rejection. This study introduces a genetic algorithm (GA)-based approach for optimizing PID controller parameters to enhance the performance of temperature control during the saponification of ethyl acetate in a CSTR, a mildly exothermic reaction characterized by second-order kinetics. The proposed method employs the integral of time-weighted absolute error (ITAE) as a fitness function to iteratively minimize system error and optimize controller gains. Comparative analysis with the ZN-tuned PID controller reveals substantial improvements using the GA-tuned PID controller, including a reduction in overshoot from 61.4% to 38.1%, and decreases in rise, peak, and settling times by 29.7%, 35.3%, and 72.02%, respectively. Additionally, the GA-PID controller demonstrates superior set-point tracking and robust disturbance rejection, achieving a system error reduction of 68.1% compared to the ZN-PID controller. These results underscore the efficacy of genetic algorithms in overcoming the limitations of conventional tuning methods for nonlinear systems. The GA-based tuning approach not only enhances control accuracy and stability but also offers a scalable solution for optimizing complex industrial processes, paving the way for advancements in chemical reactor control and broader applications in process engineering.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Genetic Algorithm-Based PID Optimization for Ethyl Acetate Saponification in a Continuous Stirred Tank Reactor

AU  - Mohamad Hassan Hamadelnil Deifalla
AU  - Gurashi Abdalla Gasmelseed
Y1  - 2024/12/31
PY  - 2024
N1  - https://doi.org/10.11648/j.ajche.20241206.11
DO  - 10.11648/j.ajche.20241206.11
T2  - American Journal of Chemical Engineering
JF  - American Journal of Chemical Engineering
JO  - American Journal of Chemical Engineering
SP  - 123
EP  - 131
PB  - Science Publishing Group
SN  - 2330-8613
UR  - https://doi.org/10.11648/j.ajche.20241206.11
AB  - Effective temperature control in continuous stirred-tank reactors (CSTRs) is essential for maintaining product quality and process stability in nonlinear chemical systems. Traditional PID controllers, tuned via Ziegler-Nichols (ZN) methods, often struggle to manage the nonlinearities of such systems, leading to high overshoot, prolonged settling times, and suboptimal disturbance rejection. This study introduces a genetic algorithm (GA)-based approach for optimizing PID controller parameters to enhance the performance of temperature control during the saponification of ethyl acetate in a CSTR, a mildly exothermic reaction characterized by second-order kinetics. The proposed method employs the integral of time-weighted absolute error (ITAE) as a fitness function to iteratively minimize system error and optimize controller gains. Comparative analysis with the ZN-tuned PID controller reveals substantial improvements using the GA-tuned PID controller, including a reduction in overshoot from 61.4% to 38.1%, and decreases in rise, peak, and settling times by 29.7%, 35.3%, and 72.02%, respectively. Additionally, the GA-PID controller demonstrates superior set-point tracking and robust disturbance rejection, achieving a system error reduction of 68.1% compared to the ZN-PID controller. These results underscore the efficacy of genetic algorithms in overcoming the limitations of conventional tuning methods for nonlinear systems. The GA-based tuning approach not only enhances control accuracy and stability but also offers a scalable solution for optimizing complex industrial processes, paving the way for advancements in chemical reactor control and broader applications in process engineering.

VL  - 12
IS  - 6
ER  -

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