S Sukiran
Electrical Engineering Department, Universitas Islam Sultan Agung

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CONTROL OF AIR COOLING SYSTEM BASED ON FUZZY LOGIC S Sukiran; Arief Marwanto; Suryani Alifah
Journal of Telematics and Informatics Vol 6, No 1: March 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (609.241 KB) | DOI: 10.12928/jti.v6i1.

Abstract

A comfortable activity in of a room is depended on environment. Temperature and humidity is considered that greatly affect the air condition performance. This study aimed to design and built a prototype air cooling controller, namely the fan, so it can control the speed of the fan according to conditions of temperature and humidity. This research uses arduino uno R3 microcontroller and the of DHT 22 sensor to detect temperature and humidity of room and PIR sensor to detect human presence in the room. Sugeno fuzzy logic method is used to take the decision which is processed by microcontroller. That an test is done by manual calculation, matlab simulation and prototype testing. The results shows the averaged accuracy of temperature testing is 3.89%, while range is 1.99% and average humidity accuracy 3.21%, range is 2.49%. the system is able to control the fan of cooling fan autamatically accordances to the desired rules based on fuzzy logic. Therefore, a proposed prototype model is able works performed.comfortable activity in of a room is depended on environment. Temperature and humidity is considered that greatly affect the air condition performance. This study aimed to design and built a prototype air cooling controller, namely the fan, so it can control the speed of the fan according to conditions of temperature and humidity. This research uses arduino uno R3 microcontroller and the of DHT 22 sensor to detect temperature and humidity of room and PIR sensor to detect human presence in the room. Sugeno fuzzy logic method is used to take the decision which is processed by microcontroller. That an test is done by manual calculation, matlab simulation and prototype testing. The results shows the averaged accuracy of temperature testing is 3.89%, while range is 1.99% and average humidity accuracy 3.21%, range is 2.49%. the system is able to control the fan of cooling fan autamatically accordances to the desired rules based on fuzzy logic. Therefore, a proposed prototype model is able works performed.