CONTROL OF ELECTRIC MOTORS USING FUZZY LOGIC THROUGH VIBRATION, SOUND FREQUENCY, AND ELECTROMAGNETIC FLUX PARAMETERS

Abstract

This study explores the application of fuzzy logic for controlling electric motors by analyzing key parameters such as vibration, sound frequency, and electromagnetic flux. Traditional motor control systems often struggle to efficiently handle the uncertain and nonlinear conditions that affect motor performance. By employing fuzzy logic, which models human-like decision-making with uncertainty, we can achieve a more responsive and adaptive control system for electric motors. Our research builds on recent advancements in fuzzy logic systems, illustrating the effectiveness of this approach through a rule-based model, simulated performance results, and specific control scenarios.