Fuzzy Controller for Speed Control of the Car

Abstract

This research document introduces an innovative approach to enhancing the speed control of cars by integrating the principles of fuzzy logic through the versatile platform of Matlab. The dataset utilized originates from the Road Transportation Office (RTO), encompassing two pivotal input variables: Speed and Distance. The speed variable adopts membership functions categorizing it as slow, medium, or fast, while distance takes on values of close, medium, or far, employing triangular membership functions. The primary objective of this paper is to automate the intricate process of applying brakes or regulating the car's speed. Achieving this involves evaluating input values for speed and distance, considering both factors to make informed decisions on whether to apply brakes, slightly engage the brakes, or refrain from braking altogether. Employing Mamdani's implication, a comprehensive fuzzy rule base is formulated. The implementation of this methodology is facilitated through the Matlab Simulink and fuzzy toolbox. Utilizing triangular membership functions contributes to the generation of forecasted results. This approach not only enhances the safety of driving by enabling the automated decision-making process but also showcases the practical application of Fuzzy Logic in real-world scenarios. The integration of Matlab Simulink and the fuzzy toolbox underscores the efficiency and applicability of this innovative solution in the realm of car speed control.