Low-Speed Performance Enhancement of Induction Motor Drives Using Mamdani Fuzzy Logic-Based V/f Control

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Authors: Alfonso A. Sevilla-Hidalgo, Erwin J. Sacoto-Cabrera, Roger Jesus Coaquira-Castillo, L. Walter Utrilla Mego, Rossy Uscamaita-Quispetupa, Yesenia Concha-Ramos, Edison Moreno-Cardenas
Cited by: 1
References: 37

Abstract

Conventional scalar voltage–frequency (V/f) control is widely adopted in industrial drives due to its simplicity and low cost; however, at very low operating frequencies, it often suffers from poor transients, speed oscillations, and excessive start-up currents when a proportional–integral controller (PIC) is used in the speed loop. These limitations hinder stable operation and reliable start-up under load, motivating the need for a more robust low-speed control scheme. This paper presents the design and experimental validation of an improved V/f scalar control based on a Mamdani fuzzy logic controller tuned by particle swarm optimization (PSO). A physical prototype was implemented using speed and current sensing and LN CO3636-3B that enables the control strategies, updates the proportional and integral gains through Mamdani inference in a discrete PI law, and drives a self-commutated inverter via PWM. Experiments were performed under variable conditions, demonstrating that the proposed controller at 6.06% of rated speed achieves stable regulation with 10% overshoot and a settling time of 0.445 s, whereas the PIC exhibits instability with steady oscillations and overshoot up to 44%. The proposed controller keeps the inrush current within the design limit below 1.615 A. Overall, the PSO-tuned Mamdani fuzzy controller improves low-speed robustness while respecting transient design constraints.

Fields of Study & Subjects

Sensorless Control of Electric Motors Fuzzy Logic and Control Systems Wind Turbine Control Systems

Publication details

Journal / source
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
14
Pages
67088–67100
Publication date
1 January 2026
Language
EN