Development of a Climate Equipment Parameter Acquisition System using PID and Fuzzy Logic Controllers to Improve Energy Efficiency

Authors

  • Marina Moseva Department of Mathematical Cybernetics and Information Technologies, Moscow Technical University of Communications and Informatics, Russia
  • Sergey Simonov Department of Mathematical Cybernetics and Information Technologies, Moscow Technical University of Communications and Informatics, Russia
  • Mikhail Gorodnichev Department of Mathematical Cybernetics and Information Technologies, Moscow Technical University of Communications and Informatics, Russia
Volume: 14 | Issue: 5 | Pages: 16840-16846 | October 2024 | https://doi.org/10.48084/etasr.8182

Abstract

Today, energy-efficient resource management is an important task. This study aims to improve the energy efficiency of the cooling system of a technical room by developing a transparent and explainable temperature adaptation tuning algorithm based on the combination of PID control and fuzzy logic methods. This work focuses on the design and development of a hardware and software system consisting of a microcontroller and a temperature sensor. This paper analyzes temperature control based on PID and fuzzy controllers and proposes a combined method to allow for more accurate temperature control tuning. The experimental results show that the combined method reduces the rise time by at least 5%, the stabilization time by at least 17%, and the power consumption by at least 21%.

Keywords:

fuzzy logic, air conditioning system, data center, energy efficiency, thermal managment, PID controller

Downloads

Download data is not yet available.

References

P. Cominos and N. Munro, "PID controllers: recent tuning methods and design to specification," IEE Proceedings - Control Theory and Applications, vol. 149, no. 1, pp. 46–53, Jan. 2002.

S. K. Pandey, K. Veeranna, B. Kumar, and K. U. Deshmukh, "A Robust Auto-tuning Scheme for PID Controllers," in IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Oct. 2020, pp. 47–52.

W. W. Shein, Y. Tan, and A. O. Lim, "PID Controller for Temperature Control with Multiple Actuators in Cyber-Physical Home System," in 2012 15th International Conference on Network-Based Information Systems, Melbourne, Australia, Sep. 2012, pp. 423–428.

N. H. A. Hamid, M. M. Kamal, and F. H. Yahaya, "Application of PID controller in controlling refrigerator temperature," in 2009 5th International Colloquium on Signal Processing & Its Applications, Kuala Lumpur, Malaysia, Mar. 2009, pp. 378–384.

Y. Hu, "MCU-Based PID Temperature Control System for Linear Heating and Cooling," Academic Journal of Science and Technology, vol. 8, no. 1, pp. 212–215, Nov. 2023.

M. Khalil, A. S. McGough, Z. Pourmirza, M. Pazhoohesh, and S. Walker, "Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption — A systematic review," Engineering Applications of Artificial Intelligence, vol. 115, Oct. 2022, Art. no. 105287.

M. Anastasiadou, V. Santos, and M. S. Dias, "Machine Learning Techniques Focusing on the Energy Performance of Buildings: A Dimensions and Methods Analysis," Buildings, vol. 12, no. 1, Jan. 2022, Art. no. 28.

R. Patel and V. Kumar, "Multilayer Neuro PID Controller based on Back Propagation Algorithm," Procedia Computer Science, vol. 54, pp. 207–214, Jan. 2015.

M. Ray, P. Samal, and C. K. Panigrahi, "Implementation of a Hybrid Technique for the Predictive Control of the Residential Heating Ventilation and Air Conditioning Systems," Engineering, Technology & Applied Science Research, vol. 12, no. 3, pp. 8772–8776, Jun. 2022.

A. Marvuglia, A. Messineo, and G. Nicolosi, "Coupling a neural network temperature predictor and a fuzzy logic controller to perform thermal comfort regulation in an office building," Building and Environment, vol. 72, pp. 287–299, Feb. 2014.

J. C. Mugisha, B. Munyazikwiye, and H. R. Karími, "Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller," in 2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY), Yilan, Taiwan, Nov. 2015, pp. 50–55.

H. Yan, Y. Xia, X. Xu, and S. Deng, "Inherent operational characteristics aided fuzzy logic controller for a variable speed direct expansion air conditioning system for simultaneous indoor air temperature and humidity control," Energy and Buildings, vol. 158, pp. 558–568, Jan. 2018.

A. Chojecki, A. Ambroziak, and P. Borkowski, "Fuzzy Controllers Instead of Classical PIDs in HVAC Equipment: Dusting Off a Well-Known Technology and Today’s Implementation for Better Energy Efficiency and User Comfort," Energies, vol. 16, no. 7, Jan. 2023, Art. no. 2967.

J. Gonzalez-Villagomez, C. Rodriguez-Donate, M. Lopez-Ramirez, R. I. Mata-Chavez, and O. Palillero-Sandoval, "Novel Iterative Feedback Tuning Method Based on Overshoot and Settling Time with Fuzzy Logic," Processes, vol. 11, no. 3, Mar. 2023, Art. no. 694.

M. M. Rahman and M. S. Islam, "Design of a Fuzzy Based Pid Algorithm for Temperature Control of An Incubator," Journal of Physics: Conference Series, vol. 1969, no. 1, Apr. 2021, Art. no. 012055.

L. I. Minchala, J. Peralta, P. Mata-Quevedo, and J. Rojas, "An Approach to Industrial Automation Based on Low-Cost Embedded Platforms and Open Software," Applied Sciences, vol. 10, no. 14, Jan. 2020, Art. no. 4696.

Z. Yu, N. Liu, K. Wang, X. Sun, and X. Sheng, "Design of Fuzzy PID Controller Based on Sparse Fuzzy Rule Base for CNC Machine Tools," Machines, vol. 11, no. 1, Jan. 2023, Art. no. 81.

K. A. Al Sumarmad, N. Sulaiman, N. I. A. Wahab, and H. Hizam, "Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers," Energies, vol. 15, no. 1, Jan. 2022, Art. no. 303.

"ESP-IDF Programming Guide - ESP32." [Online]. Available: https://docs.espressif.com/projects/esp-idf/en/latest/esp32/.

"Adafruit BME280 Library 1.0 documentation." https://docs.circuitpython.org/projects/bme280/en/latest/.

Allegro Microsystems Inc., "ACS712 - Fully Integrated, Hall Effect-Based Linear Current Sensor with 2.1 kVRMS Voltage Isolation and a Low-Resistance Current Conductor." [Online]. Available: https://www.sparkfun.com/datasheets/BreakoutBoards/0712.pdf.

J. G. Ziegler and N. B. Nichols, "Optimum Settings for Automatic Controllers," Journal of Dynamic Systems, Measurement, and Control, vol. 115, no. 2B, pp. 220–222, Jun. 1993.

V. N. Alexandrov, J. J. Dongarra, B. A. Juliano, R. S. Renner, and C. J. K. Tan, Eds., "Computational Science - ICCS 2001 Proceedings, Part II," San Francisco, CA, USA, May 2001.

Downloads

How to Cite

[1]
Moseva, M., Simonov, S. and Gorodnichev, M. 2024. Development of a Climate Equipment Parameter Acquisition System using PID and Fuzzy Logic Controllers to Improve Energy Efficiency. Engineering, Technology & Applied Science Research. 14, 5 (Oct. 2024), 16840–16846. DOI:https://doi.org/10.48084/etasr.8182.

Metrics

Abstract Views: 23
PDF Downloads: 28

Metrics Information