Design of Temperature Control in Air Conditioner Using Self-Tuning PID Based on Fuzzy-Mamdani

Main Article Content

Daniel Silitonga
Wahyudi Wahyudi

Abstract

Air Conditioner (AC) is a form of technological advancement in air conditioning. The consumption of AC in society is also very high at 48% using AC for 8-12 hours per day. This data is according to the Indonesian Consumers Foundation (YLKI). There are many factors behind this very long use. In this article try to see the AC factor that has not efficiently obtained the temperature setpoint value causing excessive use. When the AC gets the setpoint from the remote control. The actuator component in the form of a Peltier will work to achieve that value. This design will be carried out in order to create a PID control that performs tuning with the Fuzzy-Mamdani method in order to obtain the appropriate PID coefficient value. The test results from the Self-Tuning PID controller have a faster steady state time in all tests. In each test of the fixed reference value. The test of the changing reference value. and the test with the disturbance signal in the form of a step Self-Tuning PID have a faster time of 6.273 s. 3.364s and 5.4545s respectively. For the performance evaluation index, the Self-Tuning PID controller tends to have smaller ISE, IAE, and ITAE values in each test compared to the existing PID controller.

Article Details

How to Cite
Silitonga, D., & Wahyudi, W. (2025). Design of Temperature Control in Air Conditioner Using Self-Tuning PID Based on Fuzzy-Mamdani. JURNAL EDUNITRO Jurnal Pendidikan Teknik Elektro, 5(2), 91–100. https://doi.org/10.53682/edunitro.v5i2.12574
Section
Articles

References

Abdelghany. M. A.. Abdelrady Okasha Elnady. and Shorouk Ossama Ibrahim. 2023. “Optimum PID Controller with Fuzzy Self-Tuning for DC Servo Motor.” Journal of Robotics and Control (JRC) 4(4):500–508. doi:10.18196/jrc.v4i4.18676.

Abdrakhmanov. Rustam. Kamalbek Berkimbayev. Angisin Seitmuratov. Almira Ibashova. Akbayan Aliyeva. Gulira Nurmukhanbetova. and Khoja Akhmet. 2024a. Intelligent Fuzzy-PID Temperature Control System for Ensuring Comfortable Microclimate in an Intelligent Building. Vol. 15.

Abdrakhmanov. Rustam. Kamalbek Berkimbayev. Angisin Seitmuratov. Almira Ibashova. Akbayan Aliyeva. Gulira Nurmukhanbetova. and Khoja Akhmet. 2024b. Intelligent Fuzzy-PID Temperature Control System for Ensuring Comfortable Microclimate in an Intelligent Building. Vol. 15.

AFSHARİ. Faraz. 2020. “Experimental Study for Comparing Heating and Cooling Performance of Thermoelectric Peltier.” Politeknik Dergisi 23(3):889–94. doi:10.2339/politeknik.713600.

Ambroziak. Arkadiusz. and Adrian Chojecki. 2023. “The PID Controller Optimisation Module Using Fuzzy Self-Tuning PSO for Air Handling Unit in Continuous Operation.” Engineering Applications of Artificial Intelligence 117. doi:10.1016/j.engappai.2022.105485.

Attia. Abdel Hamid. Sohair F. Rezeka. and Ahmed M. Saleh. 2015. “Fuzzy Logic Control of Air-Conditioning System in Residential Buildings.” Alexandria Engineering Journal 54(3):395–403. doi:10.1016/j.aej.2015.03.023.

Belman-Flores. Juan Manuel. David Alejandro Rodríguez-Valderrama. Sergio Ledesma. Juan José García-Pabón. Donato Hernández. and Diana Marcela Pardo-Cely. 2022. “A Review on Applications of Fuzzy Logic Control for Refrigeration Systems.” Applied Sciences (Switzerland) 12(3).

Firmansyah. Muhammad Farid. and Rini Puji Astutik. 2024. Prototipe Sistem Peringatan Dan Kontrol Jaring Otomatis Dengan Metode Fuzzy Untuk Mitigasi Risiko Lepasnya Ikan Saat Banjir Di Tambak Berbasis IoT (Internet of Things) Prototype of Automatic Net Warning and Control System Using Fuzzy Method to Mitigate the Risk of Fish Release during Floods in Ponds Based on IoT (Internet of Things). Vol. 6.

Furizal. Sunardi. and Anton Yudhana. 2023. “Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things.” Journal of Robotics and Control (JRC) 4(3):308–22. doi:10.18196/jrc.v4i3.18327.

He. Zhihui. and Xiaofeng Li. 2020. “A Fuzzy Control System for Fitness Service Based on Genetic Algorithm during COVID-19 Pandemic.” Journal of Intelligent and Fuzzy Systems 39(6):8805–12. doi:10.3233/JIFS-189277.

Khokhar. Salah Ud Din. Qinke Peng. Ali Asif. Muhammad Yasir Noor. and Aaqib Inam. 2020. “A Simple Tuning Algorithm of Augmented Fuzzy Membership Functions.” IEEE Access 8:35805–14. doi:10.1109/ACCESS.2020.2974533.

Lahlouh. Ilyas. Driss Khouili. Ahmed Elakkary. and Nacer Sefiani. 2021. “Pareto Optimality Based Multi-Objective Genetic Algorithm: Application for Livestock Building System Using an Independent Pid Controller.” Engineering and Applied Science Research 48(1):83–91. doi:10.14456/easr.2021.10.

Liu. Jingru. Xin Sun. Bin Lu. Yunkun Zhang. and Rui Sun. 2016. “The Life Cycle Rebound Effect of Air-Conditioner Consumption in China.” Applied Energy 184:1026–32. doi:10.1016/j.apenergy.2015.11.100.

Maghfiroh. H.. J. S. Saputro. C. Hermanu. M. H. Ibrahim. and A. Sujono. 2021. “Performance Evaluation of Different Objective Function in PID Tuned by PSO in DC-Motor Speed Control.” IOP Conference Series: Materials Science and Engineering 1096(1):012061. doi:10.1088/1757-899x/1096/1/012061.

Xie. Hongmei. Yuxiao Yan. and Tianzi Zeng. 2022. “Simulations of Fuzzy PID Temperature Control System for Plant Factory.” Pp. 1089–99 in Lecture Notes in Electrical Engineering. Vol. 942 LNEE. Springer Science and Business Media Deutschland GmbH.

Xie. Xiao Lan. and Zhen Long. 2015a. “Fuzzy PID Temperature Control System Design Based on Single Chip Microcomputer.” International Journal of Online Engineering 11(8):29–33. doi:10.3991/ijoe.v11i8.4881.

Xie. Xiao Lan. and Zhen Long. 2015b. “Fuzzy PID Temperature Control System Design Based on Single Chip Microcomputer.” International Journal of Online Engineering 11(8):29–33. doi:10.3991/ijoe.v11i8.4881.

Zhai. Wenzheng. Liangwei Dong. and Yueli Hu. 2024. “Self-Tuning Control of Steam Sterilizer Temperature Based on Fuzzy PID and IPSO Algorithm.” Journal of Measurements in Engineering. doi:10.21595/jme.2024.24134.

Zhou. Chonggang. Zhaosong Fang. Xiaoning Xu. Xuelin Zhang. Yunfei Ding. Xiangyang Jiang. and Ying ji. 2020. “Using Long Short-Term Memory Networks to Predict Energy Consumption of Air-Conditioning Systems.” Sustainable Cities and Society 55. doi:10.1016/j.scs.2019.102000.