Performance Comparison of Fuzzy Mamdani and Sugeno in Curtain and Lighting Control

Abstract

Efficient room lighting is essential for user comfort and health. Suboptimal lighting can lead to negative effects such as eye strain and reduced productivity. This study aims to implement and compare the performance of Fuzzy Mamdani and Sugeno methods in an automatic curtain and lighting control system based on Arduino Uno. The system is designed to respond to changes in light intensity by adjusting curtains and a dimmable lamp according to values obtained from LDR sensors. Both Fuzzy Mamdani and Sugeno methods are applied to improve energy efficiency and system responsiveness. Tests were conducted under various conditions to evaluate system performance. The results show that the Sugeno method has a faster response time compared to the Mamdani method in all test scenarios. The average response time of Sugeno is 13.898 seconds, while Mamdani requires an average of 15.158 seconds, with an average difference of 1.26 seconds. In terms of accuracy, the Sugeno method also demonstrates better performance. For curtain control, Sugeno achieved an MSE of 347.9368872 and an RMSE of 18.65306643, while Mamdani recorded an MSE of 570.71862 and an RMSE of 23.889718. For dimmer control, Sugeno obtained an MSE of 1683.99071 and an RMSE of 41.0364559, outperforming Mamdani, which had an MSE of 2679.24 and an RMSE of 51.7614. This implementation provides an optimal solution for automatic lighting management to enhance energy efficiency and user comfort.