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

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 11 O C, 21% humidity, room temperature 14 O C, 41% humidity, room temperature 27 O C, 44% humidity and room temperature 33 O C, 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%.