Optimal duty ratio controller for improved DTFC of induction motor using Fuzzy logic

Sudheer, H; Sf, Kodad; Sarvesh, B.

doi:10.1109/sceecs.2016.7509321

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…The model described by sudheer et.al. in [5], [31] is used to develop Simulink model of Indcution motor.…”

Section: Conventional Direct Torque Control (Cdtc)mentioning

confidence: 99%

“…The implementation of Fuzzy duty ratio was proposed by Ivica Kuric et al [23], Y S Kishore Babu, et al [22], Sudheer H et al [24]. In most of the papers [31][32][33][34][35] the duty ratio controller is applied to CDTC for torque ripple reduction. In this paper the DRC controller using both Fuzzy and Neural Networks is developed and applied to Fuzzy DTC.…”

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

“…In this paper the DRC controller using both Fuzzy and Neural Networks is developed and applied to Fuzzy DTC. The optimal Duty ratio controller using fuzzy logic is developed as given by Sudheer H et al [31]. The basic concept of duty ratio control is applying the active switching state of VSI for just enough time to enough time to achieve the torque and flux reference values [21][22], [31].…”

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

“…The optimal Duty ratio controller using fuzzy logic is developed as given by Sudheer H et al [31]. The basic concept of duty ratio control is applying the active switching state of VSI for just enough time to enough time to achieve the torque and flux reference values [21][22], [31]. The Fuzzy duty cycle controller determines the time duration for which active voltage is applied.…”

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

See 3 more Smart Citations

Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller

Sudheer¹,

Sf²,

Sarvesh

2017

IJ-AI

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This paper presents improvements in Direct Torque control of an induction motor using Fuzzy logic with Fuzzy logic and neural network based duty ratio controller. The conventional DTC (CDTC) of induction motor suffers from major drawbacks like high torque and flux ripples and poor transient response. Torque and flux ripples are reduced by replacing hysteresis controller and switching table with Fuzzy logic switching controller (FDTC). In FDTC the selected switching vector is applied for the complete switching time period. The FDTC steady state performance can be improved by using duty ratio controller, the selected switching vector is applied only for the time determined by the duty ratio (δ) and for the remaining time period zero switching vector is applied. The selection of duty ratio using Fuzzy logic and neural networks is projected in this paper. The effectiveness proposed methods are evaluated using simulation by Matlab/Simulink.

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“…The model described by sudheer et.al. in [5], [31] is used to develop Simulink model of Indcution motor.…”

Section: Conventional Direct Torque Control (Cdtc)mentioning

confidence: 99%

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

Section: Duty Ratio Controller(drc) Using Fuzzy Logicmentioning

confidence: 99%

See 2 more Smart Citations

Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller

Sudheer¹,

Sf²,

Sarvesh

2017

IJ-AI

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show abstract

“…The results showed a reduction of 40% in torque ripples. Another strategy used in Sudheer et al consists of using a fuzzy controller to control the duty cycle to determine the optimal application duration of the appropriate voltage vector for each sampling period instead of applying it for the entire switching period. The results showed that the torque ripples were reduced significantly.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy 12 sectors improved direct torque control of a DFIG with stator power factor control strategy

Ayrir

Haddi

2019

Int Trans Electr Energ Syst

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Summary In this paper, an improved direct torque control (DTC) strategy based on a fuzzy inference system is proposed to control a doubly fed induction generator (DFIG)‐based wind energy conversion system (WECS). The proposed method is based on increasing the number of sectors to 12 instead of six in the classical DTC (C‐DTC), and the use of a fuzzy inference system to generate the optimal voltage vector to apply to the rotor side converter (RSC). The proposed method aims to reduce the flux and torque undulations which are considered the main disadvantage of the C‐DTC and to control the power factor at the stator terminals by generating the referential rotor flux from the referential reactive power. The effectiveness of the proposed strategy is well tested by the simulation. Moreover, a total harmonic distortion (THD) analysis was performed for the rotor and stator currents waveforms. The results show a considerable reduction of the undulations for both flux and torque, and a significant reduction of the THD.

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Sensorless Direct Torque Control of Induction Motor Using Neural Network-Based Duty Ratio Controller

Sudheer

Kodad

Sarvesh

2017

Advances in Systems, Control and Automation

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Optimal duty ratio controller for improved DTFC of induction motor using Fuzzy logic

Cited by 7 publications

References 13 publications

Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller

Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller

Fuzzy 12 sectors improved direct torque control of a DFIG with stator power factor control strategy

Sensorless Direct Torque Control of Induction Motor Using Neural Network-Based Duty Ratio Controller

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