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Record W2109843725 · doi:10.1109/ecce.2011.6064273

Introducing the elliptical carrier for PWM inverters: Derivation and properties for phase-shift compensation

2011· article· en· W2109843725 on OpenAlexafffund
Lucas Sinopoli, Martin Ordonez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsSimon Fraser UniversityMemorial University of Newfoundland
FundersSimon Fraser University
KeywordsSawtooth wavePulse-width modulationWaveformPhase (matter)Control theory (sociology)Pulse (music)Carrier recoveryModulation (music)Carrier signalNon-sinusoidal waveformSIGNAL (programming language)Compensation (psychology)Power (physics)PhysicsComputer scienceElectronic engineeringMathematicsOpticsTelecommunicationsAcousticsEngineeringControl (management)

Abstract

fetched live from OpenAlex

Carrier-based Sinusoidal PWM schemes have been developed in order to improve the output spectrum of power inverters, disregarding its phase characteristic. Additionally, the carriers analyzed in the literature have always consisted in triangular or sawtooth waveforms. This paper introduces a modified carrier able to manipulate the phase of the reference signal in Sinusoidal PWM while maintaining the characteristics of its frequency spectrum. The paper presents a method that can be applied to find the modified carrier for a given phase-shift by calculating the PWM pulse widths. Initially, the pulse widths are approximated to a sinusoidal function by assuming a high switching frequency, and then a recursive numerical method is proposed for moderate to low frequencies. The phase control characteristics and the nature of the elliptical carrier are studied, and finally an FFT analysis is performed to evaluate the resulting signals. The elliptical carrier is a significant contribution towards the extension of properties in carrier-based PWM modulation.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.240

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 head0.046
GPT teacher head0.239
Teacher spread0.193 · 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 designSimulation or modeling
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

Citations0
Published2011
Admission routes2
Has abstractyes

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