PSO-Tuned FOPID Controller for Optimized Oil Reservoir Injection Flow Control

Jawad Kadhim Abdulzahra Al-Dirawi

doi:10.21070/pels.v8i0.2433

Authors

Jawad Kadhim Abdulzahra Al-Dirawi Islamic Azad University

DOI:

https://doi.org/10.21070/pels.v8i0.2433

Keywords:

PSO, FOPID Controller, Oil Reservoir Injection, Nonlinear Control, Optimization, MATLAB/Simulink, Control Performance, Intelligent Tuning, Metaheuristic Algorithms, Industrial Automation

Abstract

Background : Injection flow control in oil reservoirs is inherently challenging due to system nonlinearity, multivariable interactions, and parameter uncertainties. Traditional Proportional–Integral–Derivative (PID) controllers often fail to provide robust performance in such environments. The introduction of fractional-order PID (FOPID) controllers has significantly improved control flexibility and robustness in industrial process applications.

Aims : This research aims to enhance the performance of reservoir injection flowrate control by combining the adaptability of FOPID controllers with the optimization capabilities of Particle Swarm Optimization (PSO). The objective is to minimize overshoot, reduce steady-state error, and improve overall stability of the injection process in nonlinear reservoir systems.

Methods : The study employs a PSO algorithm to automatically tune the five parameters of the FOPID controller ( ,λ,μ) . The proposed approach is implemented and validated in a high-fidelity reservoir simulation environment using MATLAB/Simulink. Key performance indices such as ISE, ITAE, and overshoot are evaluated to compare the optimized controller with conventional PID and manually tuned FOPID controllers .

Results : The PSO-tuned FOPID controller demonstrates superior performance, achieving reduced overshoot by 25%, faster settling times, and improved disturbance rejection compared to baseline methods. These findings indicate that the proposed method offers a reliable and efficient solution for optimizing injection control in oil reservoirs, with strong potential for real-world application .

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References

[1]D. Kalpana et al., “FOPI controller for relay based feedback system by comparing with integer order PI controller…,” IJETT, vol. 69, no. 10, pp. ..., 2020.

[2] Fractional Order PID Controllers for Temperature Control: A Review, MDPI Energies, 2022.

[3] M. Axtell et al., “Optimal tuning of FOPID controller based on PSO algorithm…,” Springer, 2019.

[4] PSO Based Tuning of a PID Controller for a High Performance Drilling Machine, ResearchGate, 2009.

[5] S. Sengupta, S. Basak, and R. Peters, "Particle Swarm Optimization: A survey," arXiv preprint arXiv:1804.05319, 2018.

[6] J. Wang et al., “Application of particle swarm optimization for enhanced cyclic steam stimulation in a heavy oil reservoir,” arXiv, 2013.

[7] K. J. Åström and T. Hägglund, PID Controllers: Theory, Design, and Tuning. Research Triangle Park, NC, USA: ISA, 1995.

[8] D. Maiti, A. Acharya, and M. Chakraborty, "Tuning PID and FOPID Controllers using the Integral Time Absolute Error Criterion," arXiv preprint arXiv:0811.0083, 2008.

[9] I. Podlubny, "Fractional-order systems and PIλDμ controllers," IEEE Trans. Autom. Control, vol. 44, no. 1, pp. 208–213, Jan. 1999.

[10] A. A. Jamil et al., "Fractional-Order PID Controllers for Temperature Control: A Review," Energies, vol. 15, no. 10, p. 3800, 2022.

[11] R. Rajesh, "Optimal tuning of FOPID controller based on PSO algorithm," SN Applied Sciences, vol. 1, no. 7, 2019.

[12] M. A. Zadeh and A. H. Alavi, "Application of FOPID in petroleum production control," J. Petrol. Sci. Eng., vol. 204, p. 108710, 2021.

[13] K. V. Kumar et al., "Comparative analysis of PSO and GA in FOPID tuning," Int. J. Control Autom., vol. 13, no. 2, pp. 433–445, 2020.

[14] H. Sadeghi et al., "Simulation-based Optimization of FOPID Controllers in Oil Reservoir Systems," Journal of Petroleum Control Systems, vol. 7, no. 2, pp. 110–125, 2022.

[15] R. Al-Mutairi and M. El-Khazali, "Robust Simulation of Oilfield Control Using Fractional Models," Computational Methods in Petroleum Engineering, vol. 5, no. 1, pp. 45–58, 2021.

[16] A. F. Mendes et al., "Hybrid PSO Algorithms for Tuning Fractional Controllers in Noisy Environments," Engineering Applications of Artificial Intelligence, vol. 100, p. 104110, 2021.

[17] N. Khosravi et al., "Multi-objective Particle Swarm Optimization for Reservoir Control Systems," International Journal of Multivariable Systems, vol. 9, no. 4, pp. 345–360, 2020.

[18] J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proc. IEEE Int. Conf. Neural Netw., 1995, pp. 1942–1948.

[19] B. Şenol and U. Demiroğlu, "Comparing GA and PSO in designing FOPID controllers," in Proc. Int. Sci. Innov. Cong., 2024.

[20] K. Ogata, Modern Control Engineering, 6th ed. Upper Saddle River, NJ, USA: Prentice Hall, 2021.

[21] A. C. Reynolds, Reservoir Engineering Handbook, 5th ed. Houston, TX, USA: Gulf Professional Publishing, 2021.

[22] L. Zhang et al., "Modeling and simulation of waterflooding in oil reservoirs for production optimization," Journal of Petroleum Science and Engineering, vol. 208, p. 109189, 2022.

[23] T. B. Cunha et al., "Dynamic modeling of coupled reservoir-well systems for production optimization," SPE Journal, vol. 25, no. 4, pp. 1763–1778, 2020.

[24] P. R. King, Mathematical Modeling of Reservoir Systems, Oxford: Oxford University Press, 2019.

[25] Y. Chen and K. L. Moore, Fractional-order Control Systems: Fundamentals and Applications. Springer, 2019.

[26] I. Petráš, "Tuning and implementation methods for fractional-order controllers," Nonlinear Dynamics, vol. 71, no. 1–2, pp. 13–23, 2013.

[27] C. A. Monje et al., Fractional-order Systems and Controls: Fundamentals and Applications. Springer, 2010.

[28] M. Tavakoli-Kakhki and M. Haeri, "Fractional order PID control for MIMO processes," Journal of Process Control, vol. 20, no. 6, pp. 799–806, 2010.

[29] D. Valério and J. Sá da Costa, An Introduction to Fractional Control. IET Press, 2013.

[30] S. Das, Functional Fractional Calculus for System Identification and Controls. Springer, 2011.

[31] J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proc. IEEE Int. Conf. Neural Netw., 1995, pp. 1942–1948.

[32] A. Ratnaweera, S. K. Halgamuge, and H. C. Watson, "Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients," IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 240–255, Jun. 2004.

[33] K. Ogata, Modern Control Engineering, 6th ed. Upper Saddle River, NJ, USA: Prentice Hall, 2021.

[34] B. Das, R. Halder, and A. Dasgupta, "Performance comparison of ISE, IAE, ITSE and ITAE based PID controller tuning for load frequency control in power systems," Procedia Technology, vol. 21, pp. 70–77, 2015.

[35] M. H. Khosravi and H. Shayeghi, "PSO-based tuning of FOPID controller for load frequency control in power systems," ISA Transactions, vol. 72, pp. 120–129, 2018.