Fuzzy Systems in Motor Control Solutions: A Comparative Analysis of Fuzzy Logic Vs. PI Regulators in Dynamic Load Scenarios

Abstract This paper presents a comprehensive comparative analysis of fuzzy logic and conventional PI controllers in motor control applications, focusing on dynamic load scenarios. We investigate the integration of fuzzy logic controllers within field-oriented control (FOC) architectures, particularly examining their performance in speed regulation, oscillation reduction, and transient response. Through systematic experimentation with a sensorless PMSM drive system, we demonstrate how fuzzy controllers can outperform traditional PI regulators in handling nonlinearities and varying operating conditions. The study includes detailed analysis of control surface optimization, revealing how strategic modifications to membership functions can significantly reduce speed oscillations while maintaining responsiveness. Our results show that the implemented fuzzy speed controller achieves 28.57% faster settling time compared to its PI counterpart, albeit with a 2% overshoot trade-off. Furthermore, we identify key subsystems within FOC architectures where fuzzy logic implementation offers the most substantial benefits, including open-loop start-up sequences and flux control. The paper concludes with practical insights into computational requirements for embedded implementations and discusses future directions for intelligent control systems in motor drive applications.