Articles | Volume 16, issue 1
https://doi.org/10.5194/ms-16-209-2025
https://doi.org/10.5194/ms-16-209-2025
Research article
 | 
16 Apr 2025
Research article |  | 16 Apr 2025

Research on fuzzy proportional–integral–derivative (PID) control of bolt tightening torque based on particle swarm optimization (PSO)

Xiao Cheng, Zhanghao Guo, and Jun Ke

Related subject area

Subject: Dynamics and Control | Techniques and Approaches: Mathematical Modeling and Analysis
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Cited articles

Ahmadnia, M., Hajipour, A., and Tavakoli, H.: Robust variable-order fractional PID-LP fuzzy controller for Automatic Voltage Regulator systems, Appl. Soft. Comput., 167, 112268, https://doi.org/10.1016/j.asoc.2024.112268, 2024. 
Alenizi, F. A., Abbasi, S., Hussein Mohammed, A., and Masoud Rahmani, A.: The artificial intelligence technologies in Industry 4.0: A taxonomy, approaches, and future directions, Comput. Ind. Eng., 185, 109662, https://doi.org/10.1016/j.cie.2023.109662, 2023. 
Altbawi, S. M. A., Mokhtar, A. S. Bin, Jumani, T. A., Khan, I., Hamadneh, N. N., and Khan, A.: Optimal design of Fractional order PID controller based Automatic voltage regulator system using gradient-based optimization algorithm, Journal of King Saud University – Engineering Sciences, 36, 32–44, https://doi.org/10.1016/j.jksues.2021.07.009, 2024. 
Althoefer, K., Lara, B., Zweiri, Y. H., and Seneviratne, L. D.: Automated failure classification for assembly with self-tapping threaded fastenings using artificial neural networks, Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci., 222, 1081–1095, https://doi.org/10.1243/09544062JMES546, 2008. 
An, Z., Li, D., Zhang, C., Luo, Y., and Zhang, J.: Behaviours of thermal management system with micro channels for cylindrical Lithium-ion cells under Fuzzy-PID control strategy, Appl. Therm. Eng., 233, 121089, https://doi.org/10.1016/j.applthermaleng.2023.121089, 2023. 
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Short summary
The fuzzy proportional–integral–derivative controller optimized by the particle swarm optimization algorithm eliminates steady-state error, improves response speed, and enhances both system adaptability and disturbance resistance. This approach effectively addresses the inherent uncertainties and nonlinear variations in bolt tightening processes. The average deviation between the tightening torque and target torque measures 0.108 N m, achieving a control accuracy of 0.9%.
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