Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/8998
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dc.contributor.authorRashag, H.F.
dc.contributor.authorKoh, S.P.
dc.contributor.authorAbdalla, A.N.
dc.contributor.authorTan, N.M.L.
dc.contributor.authorChong, K.H.
dc.date.accessioned2018-02-21T04:49:48Z-
dc.date.available2018-02-21T04:49:48Z-
dc.date.issued2013
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/8998-
dc.description.abstractDirect torque control based on space vector modulation (SVM-DTC) protects the DTC transient merits. Furthermore, it creates better quality steady-state performance in a wide speed range. The modified method of DTC using SVM improves the electrical magnitudes of asynchronous machines, such as minimizing the stator current distortions, the stator flux with electromagnetic torque without ripple, the fast response of the rotor speed, and the constant switching frequency. In this paper, the proposed method is based on two new control strategies for direct torque control with space vector modulation. First, fuzzy logic control is used instead of the PI torque and a PI flux controller to minimizing the torque error and to achieve a constant switching frequency. The voltages in the direct and quadratic reference frame (Vd, V q) are achieved by fuzzy logic control. In this scheme, the switching capability of the inverter is fully utilized, which improves the system performance. Second, the close loop of stator flux estimation based on the voltage model and a low pass filter is used to counteract the drawbacks in the open loop of the stator flux such as the problems saturation and dc drift. The response of this new control strategy is compared with DTC-SVM. The experimental and simulation results demonstrate that the proposed control topology outperforms the conventional DTC-SVM in terms of system robustness and eliminating the bad outcome of dc-offset.
dc.titleModified Direct torque control using algorithm control of stator flux estimation and space vector modulation based on fuzzy logic control for achieving high performance from induction motors
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