Comparative Analysis of Mamdani, Sugeno and Tsukamoto Method of Fuzzy Inference System for Air Conditioner Energy Saving

Aep Saepullah, Romi Satria Wahono

Abstract


Air Conditioner (AC) nowadays is one of the electrical equipment commonly used in human daily life to reduce the heat, especially for communities who live in the hot weather area. But in the other side, air conditioner usage has a shortage such as a huge electrical energy consumption of air conditioning and it reach 90% of the total electrical energy that was needed by a household, and that especially happen when operated at the peak load electricity time or around 17:00 until 22:00, and it will cause a deficit of power supplies for use by other household appliances. In this paper will be conducted analysis and comparison between Mamdani, Sugeno and Tsukamoto method on fuzzy inference systems to find a best method in terms of reduction in electrical energy consumption of air conditioner by using Room Temperature and Humidity as input variables and Compressor speed as output variable. In this research, experiments was performed by using crisp input of room temperature 11OC, 21% humidity, room temperature 14OC, 41% humidity, room temperature 27OC, 44% humidity and room temperature 33OC, 68% humidity. The results of experiments showed that the best method in terms of reduction in electrical energy consumption of air conditioning system is a method of Tsukamoto where the average electrical energy efficiency achieved by 74,2775%.

Full Text:

PDF

References


Armendariz, J., Ortega-Estrada, C., Mar-Luna, F., & Cesaretti, E. (2013). Dual-Axis Solar Tracking Controller Based on Fuzzy-Rules Emulated Networks and Astronomical Yearbook Records. Proceedings of the World Congress on Engineering.

Bendib, T., Djeffal, F., Arar, D., & Meguellati, M. (2013). Fuzzy-Logic-based Approach for Organic Solar Cell Parameters Extraction. Proceedings of the World Congress on Engineering.

Ibrahim, M., & Ibrahim, H. (2012). Comparison Between, Fuzzy and P&O Control for MPPT for Photovoltaic System Using Boost Converter. Journal of Energy Technologies and Policy.

Kaur, A., & Kaur, A. (2012). Comparison Of Fuzzy Logic And Neuro Fuzzy Algorithms For Air Conditioning System. International Journal of Soft Computing and Engineering (IJSCE).

Kaur, A., & Kaur, A. (2012). Comparison of Mamdani Fuzzy model and Neuro fuzzy model for air conditioning systems. International Journal of Computer Science and Information Technologies (IJCSIT).

Kaur, A., & Kaur, A. (2012). Comparison of Mamdani-Type and Sugeno-Type Fuzzy Inference System For Air Conditioning System. International Journal of Soft Computing and Engineering.

Nasution, H. (2008). Development of a Fuzzy Logic Controller Algorithm for Air-conditioning System. Telkomnika.

Nasution, H. (2011). Development of a Fuzzy Logic Controller Algorithm for Air-conditioning System. Telkomnika.

Parameshwaran, R., Karunakaran, R., Iniyan, S., & Samuel, A. A. (2008). Optimization of Energy Conservation Potential for VAV Air Conditioning System using Fuzzy based Genetic Algorithm. International Journal of Engineering and Natural Sciences (IJNES).

Prats, P. J. (2001). Development And Testing Of A Number Of Matlab Based Fuzzy System Applications. Warwick: School of Engineering, University of Warwick.

PUSDATIN KESDM. (2011). Statistik Listrik. Jakarta: Kementerian Energi Dan Sumber Daya Mineral.

Sheraz, M., & Abido, M. (2013). An Efficient Fuzzy Logic Based Maximum Power point Tracking Controller for Photovoltaic Systems. International Conference on Renewable Energies and Power Quality. ICREPQ.

Sivanandam, S. N., Sumathi, S., & Deepa, S. N. (2007). Introduction to Fuzzy Logic Using MATLAB. Verlag Berlin Heidelberg: Springer.

SNI. (2000). Nomor 03-6390-2000. Badan SNI.

Sudirman. (2011). Pengaruh Fuzzy Logic Control Dibandingkan Dengan Kontrol Konvensional Terhadap Konsumsi Energi Listrik Pada Air Conditioning. International Journal of Engineering and Natural Sciences, 171-176.

Usta Ö , M., Akyazi, & Altas , İ. (2011). Design and Performance of Solar Tracking System with Fuzzy Logic Controller. International Advanced Technologies Symposium.

Wang, F. e. (2009). Evaluation And Optimization Of Air Conditioner Energy Saving Control Considering Indoor Thermal Comfort. Eleventh International IBPSA Conference. Glasgow, Scotland: IBPSA.


Refbacks

  • There are currently no refbacks.




Journal of Intelligent Systems (JIS, ISSN 2356-3982)
Copyright © 2015 IlmuKomputer.Com. All rights reserved.