Automatic Fan Speed Control System Based on Room Temperature and Humidity Using Tsukamoto Fuzzy Logic

Controlling room temperature and humidity plays a crucial role in creating occupant comfort, but the use of conventional fans with manual speed settings is often inefficient and wasteful of energy because it is not responsive to fluctuations in environmental conditions. This study aims to design an adaptive automatic fan speed control system using the Tsukamoto Fuzzy Logic method. This system uses temperature and humidity as input variables to determine the fan rotation speed in Rotations per second (Rps). The research methodology includes designing fuzzy rules (fuzzification), inference processes, and defuzzification using the weighted average method. Testing was carried out using Python program simulations with various test data scenarios. The results showed that the system was able to model non-linear relationships effectively. In conclusion, the application of Tsukamoto Fuzzy Logic successfully created a responsive and accurate control system, which offers a balance between user comfort and energy efficiency compared to conventional methods.