A Comparative Study on the Performance of the Induction Motor with Fuzzy-Based Power Converters

Abstract

This study investigates the influence of load conditions on grid voltage stability and the performance of a proposed compensator, encompassing a 1.5 hp 4-pole induction motor (IM) exposed to grid voltage disturbances. Through rigorous grid current analysis, our research demonstrates the effective mitigation of total harmonic distortion (THD) without necessitating passive filters. The comprehensive study covers multiple facets, including control strategy optimization, fine-tuning of control parameters, component ratings, output voltage analysis, operating principles, pulse width modulation, and the integral role of the fuzzy logic controller. Specifically, it underscores the significant impact of a Predictive Torque Control-based Diode Clamped Inverter in enhancing the dynamic and steady-state performance of the IM. The research delves into traditional PTC control methods and advanced techniques, such as fuzzy and evolutionary control, addressing the persistent challenge of reducing torque ripple under varying load conditions. By implementing model prediction control-based DCI, our method achieves rapid torque response without compromising the motor’s stator characteristics. Utilizing MATLAB’s environmental package, we thoroughly evaluate motor performance across diverse scenarios, encompassing stable, and rapid load changes. Despite inherent winding impedance challenges, our proposed approach consistently delivers satisfactory output responses, contributing to a more efficient, and resilient IM performance under diverse operating conditions.