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Record W2054688428 · doi:10.1109/ccece.2010.5575194

Transformer-less five-level diode-clamped converter based active power filter with auxiliary balancing circuit

2010· article· en· W2054688428 on OpenAlexaff
Sebastien Gauthier, Francis A. Okou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsHarmonicsControl theory (sociology)Active filterTransformerComputer scienceElectronic engineeringMATLABPulse-width modulationFilter (signal processing)DiodeVoltage-controlled filterElectronic filterFilter designLow-pass filterHigh-pass filterVoltageEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper proposes a approach to filter the harmful harmonics using a five-level diode-clamped converter based shunt active power filter. A multi-level converter provides superior filtering performance however, it suffers from a voltage imbalancement in its DC-link. Therefore, a novel control method for an auxiliary balancing circuit and a pulse-width modulator are also proposed. The mathematical model of the filter is derived through its state-space equations. This model is then be used to design linear controllers. To validate the proposed filter a model was constructed and simulated in Matlab/SimPowerSystems®. Preliminary results show that the filter can effectively reduces harmonics while keeping its DC-link balanced.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.193
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2010
Admission routes1
Has abstractyes

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