Zone-reduced six-rule fuzzy speed control approach for field-oriented induction motor drives

Abstract This paper evaluates a zone-reduced rule-base simplification approach for a Mamdani-type fuzzy speed controller used in the field-oriented control of an induction motor drive. Starting from a 25-rule fuzzy controller, the rule base is reduced first to a 9-rule structure through dominant-polarity grouping and then to a 6-rule structure through macro-zone representation of the reduced input space. The reduced controllers are evaluated under identical simulation conditions using transient-response indices, integral error criteria, MATLAB profiler-based execution-time measurements, and fuzzy c-means-based decision-surface similarity analysis. The 9-rule controller provides the most favorable performance–complexity compromise among the investigated fuzzy configurations, reducing the overshoot from 1.2348 to 0.5051% and achieving the lowest IAE, ITAE, and ISE values. The 6-rule controller provides the largest relative reduction in MATLAB profiler execution time, with a 57.77% decrease compared with the 25-rule controller. The FCM-based analysis indicates structural similarity between the original and reduced decision surfaces, with R 2 values of 0.8593 and 0.8159 for the 9-region and 6-region representations, respectively. These results suggest that the proposed simplification approach can reduce fuzzy rule-base complexity for the investigated simulation case while maintaining acceptable speed-tracking performance. However, real-time embedded implementation and experimental validation are left for future work.