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Osundina, Emmanuel
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science

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Neurofuzzified Analysis on Torque Control of a Squirrel Cage Induction Machine Osundina, Emmanuel; Peter Daffin Onwe; Eluebo Emmanuel Chuka; Awominure , Ajoke Alice; Tosin Tunde Oyetayo
Journal Electrical and Computer Experiences Vol. 2 No. 1 (2024): January-June
Publisher : Tinta Emas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59535/jece.v2i1.228

Abstract

The direct torque controller (DTC) is an interesting control scheme for induction motor control. It is suitable for variable-frequency drives for torque and its consequent speed control, specifically for the calculation of the estimated Induction motor's magnetic flux and torque based on the motor's measured voltage and current. However, this scheme has a disadvantage in its implementation that makes it unsuitable for high torque applications, resulting in poor drive parameter variation, optimization, and dynamic responses when compared to field-oriented control (FOC). Fuzzy-based DTC is introduced to control. The high torque ripple nature of the direct torque-controlled induction motor improves drive performance to parameter variation, and improve transient response to step changes in torque during start-up. The neurofuzzy analysis on torque performance under load disturbance shows a transient response and a low step ripple effect. Thus, this improved scheme is recommended for a high inertia application. Such as flywheel presses and rock crushes.
Co-Authors Awominure , Ajoke Alice Eluebo Emmanuel Chuka Peter Daffin Onwe Tosin Tunde Oyetayo