Fuzzy Intelligent-Based Speed Control System for Three-Phase Induction Motor

Abstract

This work presents a Fuzzy-Proportional Integral Derivative (Fuzzy-PID) controller for speed control of a three-phase induction motor, addressing limitations in conventional controllers like PID and Fuzzy Logic Control (FLC) alone, such as sensitivity to parameter variations, chattering in enhanced Sliding Mode Control, and steady-state errors in FLC. Existing studies, including recent works like Eze et al. (2024) and Shiravani et al. (2022), have explored PID, FLC, and enhanced ISMC, but often overlook hybrid approaches that combine fuzzy intelligence with PID for improved robustness under load variations and parameter changes. This research fills this gap by developing a hybrid Fuzzy-PID controller to enhance stability, reduce overshoot, and minimize steady-state errors, validated through benchmarking against standalone PID and FLC. The fuzzy rules were clearly defined, and PID parameters were tuned to optimize the FLC system. The mathematical model of the three-phase induction motor was developed, and the Fuzzy-PID controller was implemented within a closed-loop speed control configuration. The complete system was modelled in MATLAB/Simulink, and simulations were conducted to evaluate its performance under no-load, constant load, and varying load conditions. Comparative analysis showed the Fuzzy-PID outperforming PID and FLC, with faster rise times, shorter settling times, and lower steady-state errors (e.g., 0.49-0.7%), demonstrating superior robustness. Furthermore, the robustness of the Fuzzy-PID controller was validated by varying the stator resistance, confirming minimal performance deviations. This novel hybrid approach distinguishes itself by integrating fuzzy adaptability with PID precision, offering better applicability in high-performance industrial drives compared to prior methods.