Direct Torque Control of Inverter Fed Three Phase Induction Motor by Implementing Fuzzy Logic Controller

Sabır, Ali; Kashif, Syed Abdul Rahman; Ali, Hafiz Qasim; Toqueer, Khushbakht

doi:10.1109/icetas48360.2019.9117481

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Gravitational search algorithm schemes are using to control the speed of SRM along with torque ripple minimization [24]. Neural network has the inherent property of identification [25]. In this control the error torque is fed as the input to the neural network controller.…”

Section: Genetic Neuro On Torque Ripple Reductionmentioning

confidence: 99%

Hybrid intelligent controller based torque ripple minimization in switched reluctance motor drive

Pushparajesh

Nandish²,

Marulasiddappa³

2021

Bulletin EEI

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An inherent torque ripple characterizes switched reluctance technology from conventional technology. The ultimate aim of this paper is to reduce the torque ripple of the switched reluctance motor drive using genetic neural network controller based direct torque scheme. In the proposed controller network appropriate bits of data are chosen for training and testing. The proper selection of the learning rate and momentum will help in weight adjustment. Here the error is reduced which proves that the selection of voltage vectors from the vector table is precise and its results in better torque response over a wide range of speed. The simulation results reveal that the torque ripples vary between 3.25% to 1.7% for the variation in load torque and the drive speed. The experimental results for the proposed controller reveal that the torque ripple varies between 3.7% to 2.1%. Both the simulation and hardware results illustrate the efficiency of the controller.

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Section: Genetic Neuro On Torque Ripple Reductionmentioning

confidence: 99%