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Record W2106454082 · doi:10.1109/itec.2014.6861765

A digital PWM current controller for switched reluctance motor drives

2014· article· en· W2106454082 on OpenAlexafffund
Fei Peng, Ali Emadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsControl theory (sociology)Pulse-width modulationDigital controlSwitched reluctance motorComputer scienceCurrent loopController (irrigation)Current (fluid)Noise (video)EngineeringElectronic engineeringVoltageControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

Current control is essential in SRM drives. Conventionally, hysteresis current regulation is utilized for current control in SRM drives, but it has some drawbacks including high sampling rate requirement, sensitivity to switching EMI noise, and varying switching frequency. In this paper, a digital dead-beat PWM current controller for SRM drives is proposed. An observer is introduced to guarantee both fast response and stability of the dead-beat current controller. An improved current sampling method is designed to have a more accurate current sampling and to avoid PWM delay in control loop. Simulation and experimental results show that the proposed observer increases the dynamic response and improves the performance of the current controller. The improved current sampling method avoids oscillations in the control loop. The proposed digital PWM current controller has almost the same performance as hysteresis current regulation and at the same time, avoids its drawbacks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.207
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2014
Admission routes2
Has abstractyes

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