Fuzzy Logic Optimization to Control Air Conditioner (AC) Conditions using Rule-Based Algorithm

To use an Air Conditioner (AC) unit, a remote control is needed to operate it. Currently, the built-in remote of the AC unit is still operated manually by the user. This study will build and develop an AC condition control device that is different from the built-in remote of the AC unit, where the AC condition control device that is built can control the AC condition automatically and without human intervention, by implementing the fuzzy logic algorithm and Rule-based algorithm. Similar studies have been conducted but are still limited to simulations, not yet implemented on real devices. The results obtained in this study are fuzzy logic control that is optimized using the rule-based algorithm and tested with different control times (sampling periods), namely 5 seconds and 10 minutes, using the outdoor temperature as a threshold obtained from OpenWeather data. From the experimental results, the average control error if only using fuzzy logic is 1.4% for a control time of 10 seconds and 1.37% for a control time of 10 minutes. When fuzzy logic is optimized using a rule-based algorithm, the average error is reduced to 0.81% for a control time of 10 seconds and 0.32% for a control time of 10 minutes. These findings indicate that integrating a rule-based algorithm with fuzzy logic control significantly improves the accuracy of temperature regulation in an AC system. By reducing the margin of error, this optimized approach not only improves energy efficiency but also minimizes power consumption in the long run.