MétaCan
Menu
Back to cohort
Record W2490771530 · doi:10.1109/tie.2016.2594038

A Hybrid Modulation Scheme for Dual-Output Five-Leg Indirect Matrix Converter

2016· article· en· W2490771530 on OpenAlexafffund
Mahmoud Hamouda, Handy Fortin Blanchette, Kamal Al‐Haddad

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2016
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Space vector modulationVoltageModulation (music)Rectifier (neural networks)Scalar (mathematics)Topology (electrical circuits)Computer sciencePulse-width modulationElectronic engineeringEngineeringMathematicsControl (management)Artificial neural networkPhysics

Abstract

fetched live from OpenAlex

This paper proposes a hybrid modulation method for a dual-output five-leg indirect matrix converter topology. The proposed control technique combines a space vector modulation scheme (SVPWM) applied to the rectifier stage so as to control the input currents and a new digital scalar modulation scheme (DSPWM) designed to control the two loads output voltages. A generalized expression of the output voltage references is also developed showing the capability of the proposed method to control more than two independent loads without requiring additional mathematical development. Furthermore, a new modified expression of the output voltages references is proposed to enable the correct operation of the converter under unbalanced grid voltages. Also, this paper proposes a detailed mathematical analysis that allows evaluating the effect of output loads unbalances on the input current harmonic content. Simulation and experimental results are provided to show the effectiveness of the proposed theoretical investigations and confirm the capability of the proposed method to control multiple drive systems as well as ac input currents.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score1.000

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 head0.028
GPT teacher head0.235
Teacher spread0.207 · 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.

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

Citations20
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Industrial ElectronicsSame topicMultilevel Inverters and ConvertersFrench-language works237,207