Design and simulation of speed control of an induction motor taking core loss and stray load losses into account

Dhar, Rupak Kanti; Haque, Ehtashamul; Taia, Alinavan; Sikdar, Ratan

doi:10.1109/icaee.2013.6750338

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…1 [1,[5][6][7]. The CL is represented by the resistance R c and SLL is represented by resistance R st .…”

Section: State Space Model Of Immentioning

confidence: 99%

“…Performance of the VC is also affected by variations of motor parameters and by the phenomena that are not modeled and therefore not accounted for in the model [1]. Among various losses, SLL has been often neglected in the mathematical modelling of IM.…”

Section: Introductionmentioning

confidence: 99%

“…SLL is the portion of losses in a machine which cannot be accounted for by other losses such as friction and windage loss, stator I²R loss, rotor I²R loss, and core loss. It is also defined as additional losses representing a non-negligible term in the power balance of industrial induction machines [1,2]. SLL inevitably appears in any ac machines and it has numerous sources.…”

Section: Introductionmentioning

confidence: 99%

“…Some papers have presented a method of IM speed control with considering CL and SLL [1], where PI based speed controller is used to control the speed of IM [1]. But there can be seen some problems such as overshoot in the speed response curve of PI control based IM.…”

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis between Conventional PI, Fuzzy Logic and Artificial Neural Network Based Speed Controllers of Induction Motor with Considering Core Loss and Stray Load Loss

Hazari¹,

Jahan²,

Mohammad³

et al. 2017

JMEA

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Abstract:Most of the controllers of IM (induction motor) for industrial applications have been designed based on PI controller without consideration of CL (core loss) and SLL (stray load loss). To get the precise performances of torque as well as rotor speed and flux, the above mentioned losses should be considered. Conventional PI controller has overshoot effect at the transient period of the speed response curve. On the other hand, fuzzy logic and ANN (artificial neural network) based controllers can minimize the overshoot effect at the transient period because they have the abilities to deal with the nonlinear systems. In this paper, a comparative analysis is done between PI, fuzzy logic and ANN based speed controllers to find the suitable control strategy for IM with consideration of CL and SLL. The simulation analysis is done by using Matlab/Simulink software. The simulation results show that the fuzzy logic based speed controller gives better responses than ANN and conventional PI based speed controllers in terms of rotor speed, electromagnetic torque and rotor flux of IM.

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“…1 [1,[5][6][7]. The CL is represented by the resistance R c and SLL is represented by resistance R st .…”

Section: State Space Model Of Immentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations