Optimized PID Tuning in Pyrolysis Temperature Control Using Genetic Algorithm and Particle Swarm Optimization

Authors

  • Hartono Mechatronics Engineering Department, Swiss German University
  • Yunita Umniyati Mechatronics Engineering Department, Swiss German University
  • Eka Budiarto Information Technology Department, Swiss German University
  • Henry Nasution Renewable Energy Engineering Technology, Bung Hatta University
  • Mulyadi Mechatronics Engineering Technology Department, Caltex Riau Polytechnic

DOI:

https://doi.org/10.33019/k64tmh54

Keywords:

Genetic Algorithm, Particle Swarm Optimization, PID Tuning, Pyrolysis Temperature Control

Abstract

Temperature control is crucial for maintaining stable and effective thermal treatment in pyrolysis system. For this application, Proportional-Integral-Derivative (PID) controller is frequently utilized due to its ease of use and efficiency. This study aims to evaluate and compare the performance of classical and metaheuristic tuning methods for PID controllers in pyrolysis temperature control. This work compares conventional Ziegler-Nichols (ZN) and Cohen-Coon (CC) methods with metaheuristic optimization techniques, specifically Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), for tuning PID controller parameters. The main contribution of this research is the demonstration of improved control performance and computational efficiency using PSO-based PID tuning for pyrolysis applications. Simulation results show that PID controllers that the parameters tuned by GA and PSO achieve faster and smoother responses, with small overshoot, compared to classical methods. From both methods, PSO provides balanced performance with the shortest rise time (30.66 s), fastest settling time (50.80 s), and lowest overshoot (1.15%). Although both GA and PSO can maintain the set point of 500 °C with satisfactory transient response, PSO also shows better convergence efficiency, with smaller iteration numbers and lower computational effort. The results indicate that PSO-tuned PID is suitable for pyrolysis temperature control applications.

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References

Ren-X. Yang, K. Jan, C.-T. Chen, W.-T. Chen, and K. C.-W. Wu, “Thermochemical Conversion of Plastic Waste into Fuels, Chemicals, and Value-Added Materials: A Critical Review and Outlooks,” ChemSusChem, vol. 15, no. 11, pp. e202200171, Jun. 2022.

N. Ungureanu, N.-V. Vlăduț, S.-Ș. Biriș, N.-E. Gheorghiță, and M. Ionescu, “Biomass pyrolysis pathways for renewable energy and sustainable resource recovery: A critical review of processes, parameters, and product valorization,” Sustainability, vol. 17, no. 17, 2025.

S. K. Lodhi et al., “Renewable energy technologies: Present patterns and upcoming paths in ecological power production,” Global Journal of Universal Studies, vol. 1, no. 1, pp. 108–131, Jun. 2024.

D. Aboelela, H. Saleh, A. M. Attia, Y. Elhenawy, T. Majozi, and M. Bassyouni, "Recent advances in biomass pyrolysis processes for bioenergy production: Optimization of operating conditions," Sustainability, vol. 15, no. 14, p. 11238, 2023.

A. A. Jamil, W. F. Tu, S. W. Ali, Y. Terriche, and J. M. Guerrero, “Fractional-Order PID Controllers for Temperature Control: A Review,” Energies, vol. 15, no. 10, Art. no. 3800, 2022.

R. P. Borase, D. K. Maghade, S. Y. Sondkar, and A. et al., “A review of PID control, tuning methods and applications,” International Journal of Dynamics and Control, vol. 9, pp. 818–827, 2021.

M. Ouyang, Y. Wang, F. Wu, and Y. Lin, “Continuous reactor temperature control with optimized PID parameters based on improved sparrow algorithm,” Processes, vol. 11, no. 5, 2023.

N. H. Sahrir and M. A. Mohd Basri, “Modelling and manual tuning PID control of quadcopter,” in Control, Instrumentation and Mechatronics: Theory and Practice, vol. 921. Singapore: Springer, 2022.

A. D. M. Africa, J. O. Q. Chua, and J. L. H. Solis, “PID tuning of speed controller using Ziegler–Nichols and manual method DC motor,” in Proc. 2023 IEEE 15th Int. Conf. on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Philippines, 2023, pp. 1–6.

A. R. Chaidir, Widjonarko, and B. Muslim, “Incubator for Joper Day Old Chicks with Cohen-Coon PID Controller,” Jurnal Nasional Teknik Elektro, vol. 14, no. 3, pp. 100–106, 2025.

K. S. Kula, “Tuning a PI/PID controller with direct synthesis to obtain a non-oscillatory response of time-delayed systems,” Applied Sciences, vol. 14, no. 13, 2024.

H. Hartono, E. Budiarto, and H. Nasution, “Design of PID controller using LQR-based parameter selection for DC motor position control,” Jurnal Ecotipe, vol. 12, no. 1, pp. 11–19, Apr. 2025.

L. Bhardwaj, A. Mishra, and D. Asija, “Parameter optimisation of PID controller utilised for speed control of DC motor using Ziegler–Nichols and Cohen–Coon tuning method,” Advances in Smart Communication and Imaging Systems, Boca Raton, FL, USA: CRC Press, 2023.

F. Z. M. Ridha, W. S. Hacham, and M. H. O. Ajam, “Optimizing indoor temperature control using genetic algorithm for PID tuning,” NTU Journal of Renewable Energy, vol. 9, no. 1, pp. 1–11, Jul. 2025.

D. Sathya, G. Saravanan, and R. Thangamani, “Fuzzy logic and its applications in mechatronic control systems,” in Computational Intelligent Techniques in Mechatronics, K. B. Prakash, S. K. Peddapelli, I. C. K. Tam, W. L. Woo, and V. Jain, Eds., 2024.

D. Gahane, D. Biswal, and S. A. Mandavgane, “Life cycle assessment of biomass pyrolysis,” BioEnergy Research, vol. 15, pp. 1387–1406, Sep. 2022.

B. Muharto, F. R. Saputro, W. Prabowo, T. Anggoro, A. B. Adiprabowo, I. Masfuri, and B. B. Irawan, “Pyrolysis process control: Temperature control design and application for optimum process operation,” International Journal of Electrical and Computer Engineering (IJECE), vol. 14, no. 2, pp. 1473–1485, Apr. 2024.

Published

30.04.2026

How to Cite

[1]
Hartono, Yunita Umniyati, Eka Budiarto, Henry Nasution, and Mulyadi, “Optimized PID Tuning in Pyrolysis Temperature Control Using Genetic Algorithm and Particle Swarm Optimization”, JurnalEcotipe, vol. 13, no. 1, Apr. 2026, doi: 10.33019/k64tmh54.

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