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Development of a Particle Swarm Optimization-Based PI Controller for Temperature Control of a Continuous Stirred Tank Reactor in the Petrochemical Industry
Subject area: Science,Engineering and Technology · Area of research: Process Control Engineering
Abstract
Continuous Stirred Tank Reactors (CSTRs) are important process units in the petrochemical industry, where effective temperature and concentration control is essential for maintaining product quality, process safety, and operational efficiency. The nonlinear characteristics of CSTRs, coupled with process disturbances and variations in operating conditions, can make conventional Proportional-Integral (PI) controller tuning difficult. This paper presents a conceptual development of a Particle Swarm Optimization (PSO)-based PI controller for temperature control of a CSTR. The developed approach combines the simple structure of a PI controller with the optimization capability of PSO to determine suitable proportional and integral gains. The CSTR dynamic is model from material and energy balances, and the controller-design problem is expressed as an optimization problem in which the PI parameters are selected to minimize a transient response function. Performance indices including rise time, settling time, overshoot, where experimented in the controller. Results shows that conventional PI controller have a rise time of 7.2363, settling time of 16.223, and an overshoot of 0. While the PSO-Based PI have a rise time of 1.0689, a settling time of 8.2958 and an overshoot of 4.5456. The results shows that the PSO-Based PI controller have a best performance when compared to the conventional PI controller. The conceptual framework provides a basis for implementation in MATLAB/Simulink and subsequent experimental validation. The developed PSO-Based PI strategy is expected to provide systematic controller tuning and potentially improve transient regulation compared with manually or conventionally tuned PI control. This paper present a practical methodology for evaluating PSO optimization-based PI tuning for nonlinear chemical process applications.
Keywords
CSTR; Particle-Swarm-Optimization; PI-Controller; MATLAB/Simulink
References
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How to cite this paper
@article{1723319,
author = {Nwiwure, Don Basil Emmanuel, Nwigbo, Mepbari, Iue, Friday, Muele Toesae Sunday, Ndam Efeeloo},
title = {Development of a Particle Swarm Optimization-Based PI Controller for Temperature Control of a Continuous Stirred Tank Reactor in the Petrochemical Industry},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {2488-2493},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723319.pdf},
abstract = {Continuous Stirred Tank Reactors (CSTRs) are important process units in the petrochemical industry, where effective temperature and concentration control is essential for maintaining product quality, process safety, and operational efficiency. The nonlinear characteristics of CSTRs, coupled with process disturbances and variations in operating conditions, can make conventional Proportional-Integral (PI) controller tuning difficult. This paper presents a conceptual development of a Particle Swarm Optimization (PSO)-based PI controller for temperature control of a CSTR. The developed approach combines the simple structure of a PI controller with the optimization capability of PSO to determine suitable proportional and integral gains. The CSTR dynamic is model from material and energy balances, and the controller-design problem is expressed as an optimization problem in which the PI parameters are selected to minimize a transient response function. Performance indices including rise time, settling time, overshoot, where experimented in the controller. Results shows that conventional PI controller have a rise time of 7.2363, settling time of 16.223, and an overshoot of 0. While the PSO-Based PI have a rise time of 1.0689, a settling time of 8.2958 and an overshoot of 4.5456. The results shows that the PSO-Based PI controller have a best performance when compared to the conventional PI controller. The conceptual framework provides a basis for implementation in MATLAB/Simulink and subsequent experimental validation. The developed PSO-Based PI strategy is expected to provide systematic controller tuning and potentially improve transient regulation compared with manually or conventionally tuned PI control. This paper present a practical methodology for evaluating PSO optimization-based PI tuning for nonlinear chemical process applications.},
keywords = {CSTR; Particle-Swarm-Optimization; PI-Controller; MATLAB/Simulink},
month = {September},
}