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Automatic control of constant temperature and humidity in building air conditioning systems based on frequency domain analysis

Department of Architectural Engineering, Shijiazhuang University of Applied Technology, Shijiazhuang 050081, China

Received: 3 Feb 2024; Revised: 28 Mar 2024; Accepted: 15 Apr 2024; Available online: 2 May 2024; Published: 1 Jul 2024.
Editor(s): H Hadiyanto, Sohail Nadeem
Open Access Copyright (c) 2024 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

How to solve their automatic control of constant temperature and humidity gradually becomes a research hotspot as the continuous upgrading of air conditioning systems. This study aims to optimize the traditional proportional-integral-differential controller for improvement to solve the time-delay instability phenomenon in temperature and humidity control. The objective of this study is to optimize existing proportional-integral-differential controllers to improve the time-delay instability problem that is common in temperature and humidity control. Firstly, it treats the controlled object as a first-order and second-order system with time-delay characteristics. Next, the Smith predictor controller is generalized equivalent to ensure that the equivalent system does not contain time-delay. Finally, an analysis of the first-order and second-order closed-loop control system is conducted by combining Smith predictive controller and proportional-integral-differential controller. The system achieves the goal of automatic control of constant temperature and humidity by adjusting the control parameters. The experiment showcased that the temperature control time of the proposed control scheme under first-order and second-order time-delays was 16 s and 3 s, respectively. Meanwhile, the humidity control time was 14 s and 13 s, respectively. In practical applications, the proposed control scheme achieved good control effects in all four seasons. This indicates that the controller designed in this study possesses good control performance. It also can achieve the goal of constant temperature and humidity control. This can provide technical support for the automation control of air conditioning systems.

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Keywords: Frequency domain analysis; Temperature; Predictive controller; Automation;

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  1. Al-Manthria, I., Al-Ismailia, A. M., Kotagamab, H., Khanc, M., & Jeewanthad, L. J. (2021). Water, land, and energy use efficiencies and financial evaluation of air conditioner cooled greenhouses based on field experiments. Journal of Arid Land, 13(4), 375-387. https://doi.org/10.1007/s40333-021-0060-y
  2. Bushnag, A. (2023). An improved air quality and climate control monitoring system using fuzzy logic for enclosed areas. Journal of Ambient Intelligence and Humanized Computing, 14(5), 6339-6347. https://doi.org/10.1007/s12652-022-03814-z
  3. Bandewad, G., Datta, K. P., Gawali, B. W., & Pawar, S. N. (2023). Review on discrimination of hazardous gases by smart sensing technology. Artificial Intelligence and Applications, 1(2), 86-97. https://doi.org/10.47852/bonviewAIA3202434
  4. Chen, Y., Zhang, B., Qiu, D., & Xie, F. (2023). A unified frequency domain model of analog and digital PWM DC-DC converter considering PWM delay. IEEE Transactions on Power Electronics, 38(12), 15390-15405. https://doi.org/10.1109/TPEL.2023.3312694
  5. Deniz, F. N. (2022). An effective Smith predictor based fractional-order PID controller design methodology for preservation of design optimality and robust control performance in practice. International Journal of Systems Science, 53(14), 2948-2966. https://doi.org/10.1080/00207721.2022.2067366
  6. Furizal, F., Sunardi, S., Yudhana, A., & Umar, R. (2024). Energy efficiency with Internet of Things based fuzzy inference system for room temperature and humidity regulation. International Journal of Engineering, 37(1), 187-200. https://doi.org/10.5829/IJE.2024.37.01A.17
  7. Gallardo, J. M., Bellone, G., Acevedo, R., & Risk, M. (2021). Ultra-short-term heart rate variability analysis: Comparison between Poincare and frequency domain methods. IEEE Latin America Transactions, 20(1), 180-188. https://doi.org/10.1109/TLA.2022.9662187
  8. Hussain, T. (2023). Optimization and comparative performance analysis of conventional and desiccant air conditioning systems regenerated by two different modes for hot and humid climates: Experimental investigation. Energy and Built Environment, 4(3), 281-296. https://doi.org/10.1016/j.enbenv.2022.01.003
  9. Hao, J., Dai, X., Yang, L., Liao, R., Gao, J., Du, Y., & Deng, Y. (2021). Physical mechanism analysis of conductivity and relaxation polarization behavior of oil-paper insulation based on broadband frequency domain spectroscopy. IEEE Transactions on Dielectrics and Electrical Insulation, 28(5), 1571-1578. https://doi.org/10.1109/TDEI.2021.009618
  10. Hou, C., Liu, G., Tian, Q., Zhou, Z., Hua, L., & Lin, Y. (2022). Multisignal modulation classification using sliding window detection and complex convolutional network in frequency domain. IEEE Internet of Things Journal, 9(19), 19438-19449. https://doi.org/10.1109/JIOT.2022.3167107
  11. Hermawan, S., Rahmawati, S., Aditia, Q., Wibowo, B., & Yuswanto, A. (2023). Designing a water temperature control and monitoring system for Vaname shrimp cultivation based on the Internet of Things (IoT). Komets: Jurnal Komputer dan Elektro Sains, 1(1), 14-17. https://doi.org/10.58291/komets.v1i1.96
  12. He, X., & Shen, D. (2023). Distributed iterative learning temperature control for large-scale buildings. International Journal of Robust and Nonlinear Control, 33(7), 4210-4227. https://doi.org/10.1002/rnc.6259
  13. Jiang, T., Ju, P., Wang, C., & Liu, J. (2020). Coordinated control of air-conditioning loads for system frequency regulation. IEEE Transactions on Smart Grid, 12(1), 548-560. https://doi.org/10.1109/TSG.2020.3022010
  14. Kang, G. H., Kim, K. S., Chang, C. Y., & Kim, C. S. (2024). Reliability evaluation of air dryer control printed circuit board for electric multiple unit by accelerated life test. Journal of Electrical Engineering & Technology, 19(1), 821-830. https://doi.org/10.1007/s42835-023-01447-6
  15. Kim, D. E., Li, A., Dau, M. N., Kim, H. H., & Chung, W. Y. (2022). Deep learning-based smith predictor design for a remote grasping control system. Journal of Mechanical Science and Technology, 36(5), 2533-2545. https://doi.org/10.1007/s12206-022-0435-9
  16. Korupu, V. L., & Muthukumarasamy, M. (2022). A comparative study of various Smith predictor configurations for industrial delay processes. Chemical Product and Process Modeling, 17(6), 701-732. https://doi.org/10.1515/cppm-2021-0026
  17. Laifa, S., Boudjehem, B., & Gasmi, H. (2022). Direct synthesis approach to design fractional PID controller for SISO and MIMO systems based on Smith predictor structure applied for time-delay non integer-order models. International Journal of Dynamics and Control, 10(3), 760-770. https://doi.org/10.1007/s40435-021-00831-2
  18. Lu, Z., & Jiao, Y. (2022). Efficiently all-digital code tracking for band-limited DSSS systems. IEEE Communications Letters, 27(2), 686-690. https://doi.org/10.1109/LCOMM.2022.3222296
  19. Liu, H., Xie, H., Luo, H., Qi, J., Goh, H. H., & Rahman, S. (2021). Optimal strategy for participation of commercial HVAC systems in frequency regulation. IEEE Internet of Things Journal, 8(23), 17100-17110. https://doi.org/10.1109/JIOT.2021.3076434
  20. Morelli, E. A., & Grauer, J. A. (2020). Practical aspects of frequency-domain approaches for aircraft system identification. Journal of Aircraft, 57(2), 268-291. https://doi.org/10.2514/1.C035599
  21. Nagarsheth, S. H., & Sharma, S. N. (2020). The combined effect of fractional filter and Smith Predictor for enhanced closed-loop performance of integer order time-delay systems: Some investigations. Archives of Control Sciences, 30(1), 47-76. https://doi.org/10.24425/acs.2020.132585
  22. Perez, R. R., Batlle, V. F., & Hernandez, J. S. (2021). State feedback temperature control based on a Smith predictor in a precalciner of a cement kiln. IEEE Latin America Transactions, 19(1), 138-146. https://doi.org/10.1109/TLA.2021.9423857
  23. Qiao, S., Yang, Q., Wu, J., Zhan, X., & Yan, H. (2023). An approach for the stability of communication constrained networked time-delay control systems. International Journal of Control, Automation and Systems, 21(4), 1062-1069. https://doi.org/10.1007/s12555-021-0737-1
  24. Rajeshwaran, S., Kumar, C., & Ganapathy, K. (2023). Hybrid optimization based PID controller design for unstable system. Intelligent Automation & Soft Computing, 35(2), 1611-1625. https://doi.org/10.32604/iasc.2023.029299
  25. Rumalutur, S., & Mappa, A. (2019). Temperature and humidity moisture monitoring system with Arduino R3 and DHT 11. Electro Luceat, 5(2), 40-47. https://doi.org/10.32531/jelekn.v5i2.154
  26. Shang, F., Ji, Y., & Peng, W. (2022). Adaptive backstepping controller design for the air handling units of the HVAC system. Numerical Heat Transfer, Part A: Applications, 83(10), 1095-1110. https://doi.org/10.1080/10407782.2022.2102374
  27. Sah, S. K., Murugesan, K., & Elangovan, R. (2021). Optimization of energy consumption for indoor climate control using Taguchi technique and utility concept. Science and Technology for the Built Environment, 27(10), 1473-1491. https://doi.org/10.1080/23744731.2021.1924856
  28. Setyawan, A., Najmudin, H., Badarudin, A., & Sunardi, C. (2022). Evaluation of split-type air conditioner performance under constant outdoor moisture content and varied dry-bulb temperature. International Journal of Heat & Technology, 40(5), 1277-1286. https://doi.org/10.18280/ijht.400521
  29. Shruti, P., Praveen, Y. G., Vipin, C. P., & Babu, B. C. (2021). Analytical tuning of 2-DOF smith predictor control scheme for DC-DC boost converter: A process control perspective. International Journal of Circuit Theory and Applications, 49(3), 641-655. https://doi.org/10.1002/cta.2966
  30. Waworundeng, J., & Limbong, W. H. (2020). AirQMon: Indoor air quality monitoring system based on microcontroller, android, and IoT. Cogito Smart Journal, 6(2), 251-261. https://doi.org/10.31154/cogito.v6i2.213.251-261
  31. Wibawa, I. M. S., & Putra, I. K. (2022). Design of air temperature and humidity measurement based on Arduino ATmega 328P with DHT22 sensor. International Journal of Physical Sciences and Engineering, 6(1), 9-17. https://doi.org/10.53730/ijpse.v6n1.3065
  32. Wu, H., & Wong, J. W. C. (2020). Current challenges for shaping the sustainable and mold‐free hygienic indoor environment in humid regions. Letters in Applied Microbiology, 70(6), 396-406. https://doi.org/10.1111/lam.13291
  33. Wu, Y., Zhang, S., Liu, H., & Cheng, Y. (2023). Thermal sensation and percentage of dissatisfied in thermal environments with positive and negative vertical air temperature differences. Energy and Built Environment, 4(6), 629-638. https://doi.org/10.1016/j.enbenv.2022.06.002
  34. Zhang, B. (2022). Research on intelligent control system of air conditioning based on Internet of Things. International Journal of Advanced Computer Science and Applications, 13(9), 803-814. https://doi.org/10.14569/IJACSA.2022.0130994
  35. Zaki, O. M., El-Morsi, M., & Abdelaziz, O. (2024). Unlocking energy savings and emissions reduction: A comparative study of fixed-speed and variable-speed room air conditioners in high ambient temperature environments. Science and Technology for the Built Environment, 30(2), 153-171. https://doi.org/10.1080/23744731.2023.2291006
  36. Zhang, D., Li, C., Luo, S., Luo, D., Shahidehpour, M., Chen, C., & Zzhou, B. (2022). Multi-objective control of residential HVAC loads for balancing the User’s comfort with the frequency regulation performance. IEEE Transactions on Smart Grid, 13(5), 3546-3557. https://doi.org/10.1109/TSG.2022.3171847
  37. Zhang, J., Wang, F., Wen, G. (2023). Bipartite consensus for networked Euler–Lagrange systems with cooperative–competitive interactions and time delays. IET Control Theory & Applications, 17(9), 1214-1226. https://doi.org/10.1049/cth2.12451
  38. Zhang, X., Kim, D., Bang, J., & Lee, J. (2021). Time delay compensation of a robotic arm based on multiple sensors for indirect teaching. International Journal of Precision Engineering and Manufacturing, 22(11), 1841-1851. https://doi.org/10.1007/s12541-021-00542-w
  39. Zhang, Y., Yan, T., Xu, X., Gao, J., & Huang, G. (2023). Room temperature and humidity decoupling control of common variable air volume air-conditioning system based on bilinear characteristics. Energy and Built Environment, 4(3), 354-367. https://doi.org/10.1016/j.enbenv.2022.02.005
  40. Zheng, M., Zhang, G., & Huang, T. (2021). Tuning of fractional complex-order direct current motor controller using frequency domain analysis. Mathematical Methods in the Applied Sciences, 44(4), 3167-3181. https://doi.org/10.1002/mma.6653

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