Temperature Control System Design Via Fuzzy PID
DOI:
https://doi.org/10.54097/gq1w0245Keywords:
Fuzzy Logic, PID controller, Simulink, Adaptability.Abstract
This paper investigates the integration of Fuzzy Logic with PID (Proportional, Integral, Derivative) controllers to enhance the performance of temperature control systems. Traditional PID controllers, widely used in various applications, often encounter difficulties with nonlinear, time-varying, and uncertain systems, resulting in performance issues like oscillations and overshoots. To mitigate these challenges, the adoption of Fuzzy PID control, which improves adaptability, robustness, and responsiveness by incorporating fuzzy logic into the control mechanism. The study involves simulations using Simulink to compare three distinct control models: conventional PID, standalone Fuzzy Control, and the hybrid Fuzzy PID Control across standardized control scenarios. Our results show that Fuzzy PID controllers significantly outperform traditional methods, especially in complex environments lacking precise mathematical modeling. The enhanced system response times and stability demonstrated by Fuzzy PID controllers suggest substantial potential for broader application across diverse industries, promising considerable improvements in operational efficiency and reliability.
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References
Aborisade, D. O., & Stephen, O. P. (2014). Poultry house temperature control using Fuzzy-PID controller. International Journal of Engineering Trends and Technology, 11 (6), 310 - 314. DOI: https://doi.org/10.14445/22315381/IJETT-V11P259
Cai, W., & Meng, Q. (2010). Based on PLC temperature PID-Fuzzy control system design and simulation. In 2010 International Conference on Information, Networking and Automation (Vol. 2, pp. V2 - 417). IEEE.
Chu, C. W., Zhu, Z. C., Bian, H. T., & Jiang, J. C. (2021). Design of self-heating test platform for sulfide corrosion and oxidation based on Fuzzy PID temperature control system. Measurement and Control, 54 (5-6), 1082 - 1096. DOI: https://doi.org/10.1177/00202940211020338
Wu, T. Y., Jiang, Y. Z., Su, Y. Z., & Yeh, W. C. (2020). Using simplified swarm optimization on multiloop fuzzy PID controller tuning design for flow and temperature control system. Applied Sciences, 10 (23), 8472. DOI: https://doi.org/10.3390/app10238472
Zhu, X., Zhao, Z., Wei, X., & Others. (2021). Action recognition method based on wavelet transform and neural network in wireless network. In 2021 5th International Conference on Digital Signal Processing (pp. 60 - 65). DOI: https://doi.org/10.1145/3458380.3458391
Chen, J., Lu, Q., Bai, J., Xu, X., Yao, Y., & Fang, W. (2021). A temperature control method for microaccelerometer chips based on genetic algorithm and fuzzy PID control. Micromachines, 12 (12), 1511. DOI: https://doi.org/10.3390/mi12121511
Cao, Y., Zhong, C., & Qiu, K. (2016). Design and experiment about temperature control system of sealing machine based on Fuzzy PID. In 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (Vol. 2, pp. 308 - 311). DOI: https://doi.org/10.1109/IHMSC.2016.221
Baloch, M. A., Saad, N., Ismail, I., & Baloch, T. M. (2010). Design and analysis of PI-fuzzy controller for temperature control system. In 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation (pp. 378 - 383). DOI: https://doi.org/10.1109/AMS.2010.82
Zhen, Z., & Yan, G. A. (2013). Design of the fuzzy PID controller for the hot runner temperature control system. In Proceedings of the 32nd Chinese Control Conference (pp. 3464 - 3469).
Mote, T. P., & Lokhande, S. D. (2012). Temperature control system using ANFIS. International Journal of Soft Computing and Engineering, 2 (1), 2231 - 307.
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