MOGWO-FOPID: Multi-Objective Gray Wolf Optimization Fractional Order PID Controllers in Quadruple Tank Process

Asma Mustafa Mehdi Al-Salehi; Hamed Agahi

doi:10.51173/jt.v7i4.2706

Authors

Asma Mustafa Mehdi Al-Salehi Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Islamic Republic of Iran
Hamed Agahi Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Islamic Republic of Iran

DOI:

https://doi.org/10.51173/jt.v7i4.2706

Keywords:

Quadruple Tank Process (QTP), Fractional Order Proportional Integral Derivative (FOPID), Multi-Objective Optimization Algorithm

Abstract

The Quadruple Tank Process (QTP) is a laboratory model consisting of four interconnected water tanks, commonly used for control training and research purposes. The proficient regulation of the QTP is imperative, and a variety of controllers, including decentralized proportional-integral controllers, proportional controllers, integral controllers, derivative controllers, and integral-derivative-proportional controllers, are extensively utilized. A Fractional Order PID (FOPID) controller's effectiveness is largely determined by the precise organization of its parameters. This manuscript presents a Multi-Objective Gray Wolf Optimization Fractional Order PID (MOGWO-FOPID) framework, which employs the MOGWO algorithm to enhance the optimization of FOPID controller parameters for the QTP. The suggested methodology was executed and evaluated utilizing MATLAB, with its performance benchmarked against pre-existing, well-established tuning methodologies. Simulation findings indicated that the MOGWO-FOPID technique surpassed conventional methods. This superiority was corroborated through a variety of evaluation metrics, particularly emphasizing the Spacing Metric (SP) and Non-uniformity of Pareto Front (NPF) analysis. The outcomes reveal considerable advancements in both system stability and performance when employing the proposed methodology, thereby offering a more efficacious strategy for the optimization of FOPID parameters in the QTP.

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Author Biographies

Asma Mustafa Mehdi Al-Salehi, Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Islamic Republic of Iran

Hamed Agahi, Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Islamic Republic of Iran

References

M. P. Wachowiak, R. Smolíková, Y. Zheng, J. M. Zurada, and A. S. Elmaghraby, "An approach to multimodal biomedical image registration utilizing particle swarm optimization," IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 289-301, 2004.

Q. Wang, D. A. Savić, and Z. Kapelan, "Hybrid metaheuristics for multi-objective design of water distribution systems," Journal of Hydroinformatics, vol. 16, no. 1, pp. 165-177, 2014.

Z. Bingul and O. Karahan, "Comparison of PID and FOPID controllers tuned by PSO and ABC algorithms for unstable and integrating systems with time delay," Optimal Control Applications and Methods, vol. 39, no. 4, pp. 1431-1450, 2018.

V. Kumarasamy, V. Karumanchetty Thottam Ramasamy, G. Chandrasekaran, G. Chinnaraj, P. Sivalingam, and N. S. Kumar, "A review of integer order PID and fractional order PID controllers using optimization techniques for speed control of brushless DC motor drive," International Journal of System Assurance Engineering and Management, vol. 14, no. 4, pp. 1139-1150, 2023.

P. S. Krishna and P. G. K. Rao, "Fractional-order PID controller for blood pressure regulation using genetic algorithm," Biomedical Signal Processing and Control, vol. 88, p. 105564, 2024.

A. Ahuja, S. Narayan, and J. Kumar, "Robust FOPID controller for load frequency control using Particle Swarm Optimization," in 2014 6th IEEE Power India International Conference (PIICON), 2014: IEEE, pp. 1-6.

S. M. A. Altbawi, A. S. B. Mokhtar, T. A. Jumani, I. Khan, N. N. Hamadneh, and A. Khan, "Optimal design of fractional-order PID controller-based automatic voltage regulator system using gradient-based optimization algorithm," Journal of King Saud University-Engineering Sciences, 2021.

L. H. Abood and B. K. Oleiwi, "Design of fractional order PID controller for AVR system using whale optimization algorithm," Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 3, pp. 1410-1418, 2021.

K. Vanchinathan and N. Selvaganesan, "Adaptive fractional order PID controller tuning for brushless DC motor using artificial bee colony algorithm," Results in Control and Optimization, vol. 4, p. 100032, 2021.

S. Ekinci, D. Izci, and B. Hekimoğlu, "Henry gas solubility optimization algorithm-based FOPID controller design for automatic voltage regulator," in 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), 2020: IEEE, pp. 1-6.

K. A. Tehrani et al., "Design of fractional order PID controller for boost converter based on multi-objective optimization," in Proceedings of 14th International Power Electronics and Motion Control Conference EPE-PEMC 2010, 2010: IEEE, pp. T3-179-T3-185.

S. Gad, H. Metered, A. Bassuiny, and A. Abdel Ghany, "Multi-objective genetic algorithm fractional-order PID controller for semi-active magnetorheologically damped seat suspension," Journal of Vibration and Control, vol. 23, no. 8, pp. 1248-1266, 2017.

O. I. Mustafa and S. ÖKDEM, “Design and Implementation of a Wireless Sensor Network for Real Time Monitoring Applications”, EETJ, vol. 2, no. 1, pp. 42–46, Jan. 2025.

H. Chhabra, V. Mohan, A. Rani, and V. Singh, "Multi-objective cuckoo search algorithm-based 2-DOF FOPD controller for robotic manipulator," in Advances in Signal Processing and Communication: Select Proceedings of ICSC 2018, 2019: Springer, pp. 345-352.

A. Fathy, D. Yousri, H. Rezk, S. B. Thanikanti, and H. M. Hasanien, "A robust fractional-order PID controller based load frequency control using modified hunger games search optimizer," Energies, vol. 15, no. 1, p. 361, 2022.

A. Kumar and S. Suhag, "Whale optimisation algorithm tuned fractional order PIλDμ controller for load frequency control of multi-source power system," International Journal of Bio-Inspired Computation, vol. 13, no. 4, pp. 209-221, 2019.

A. X. R. Irudayaraj et al., "A Matignon’s theorem-based stability analysis of hybrid power system for automatic load frequency control using atom search optimized FOPID controller," IEEE Access, vol. 8, pp. 168751-168772, 2020.

S. Mirjalili, S. M. Mirjalili, and A. Lewis, "Grey wolf optimizer," Advances in engineering software, vol. 69, pp. 46-61, 2014.

Yasser Emad Salman, A. Y. Daeef, A. G. Perera, and Ali Al-Naji, “Computer Vision for Automated Facial Characteristics Detection”, EETJ, vol. 1, no. 1, pp. 13–19, Jun. 2024.

S. Saremi, S. Mirjalili, and A. Lewis, "Grasshopper optimisation algorithm: theory and application," Advances in engineering software, vol. 105, pp. 30-47, 2017.

E. Atashpaz-Gargari and C. Lucas, "Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition," in 2007 IEEE congress on evolutionary computation, 2007: IEEE, pp. 4661-4667.