Egg Incubator Temperature and Humidity Control Using Fuzzy Logic Controller

Yulian Zetta Maulana; Firdaus Fathurrohman; Gunawan Wibisono

doi:10.29207/resti.v7i2.4728

Yulian Zetta Maulana Institut Teknologi Telkom Purwokerto
Firdaus Fathurrohman Institut Teknologi Telkom Purwokerto
Gunawan Wibisono Institut Teknologi Telkom Purwokerto

DOI: https://doi.org/10.29207/resti.v7i2.4728

Keywords: Egg Incubator, Fuzzy Controller, Mean Squared Error, Temperature Humidity

Abstract

Controlling room temperature and humidity in egg incubator systems is a process that is widely used in the farm. A good temperature and humidity for standard egg hatching is between 35℃ – 40℃, with humidity in the machine ranging from 50%-60%. The main problems of our research is to find the robustness of the fuzzy logic controller, using the proper parameter. Because while the particular parameter is applicable for one case, but after using several times, the controller lost its robustness. Therefore, this study aims to create a system to control the temperature and humidity of the egg incubator with fuzzy control using the Sugeno methods. In order to get the input and output values, namely by connecting the DHT22 sensor to measure temperature and humidity to be processed into the microcontroller, the value obtained from the sensor will then be processed. The use of fuzzy control is used to make several stages, namely fuzzification, rule, and defuzzification which after processing will be used as output weights for the actuators used. In order to get the robust parameter, test was carried out 5 times with a test time of 18 minutes to get a stable value from the tool. By applying this, it can be concluded whether the system is reliable during different situation. The result shows that the average time for the system to get a stable humidity is 302 second. On the other hand, the average time for the system to get stable temperature is 342 second. The Mean Squared error for temperature is 1,715, while the Mean Squared Error for Humidity is 5,294. It can be concluded that the system controlled by fuzzy controller is robust, has a fast response and reliable.

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