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Record W1968541431 · doi:10.1049/iet-pel.2014.0775

Generalised approach for predictive control with common‐mode voltage mitigation in multilevel diode‐clamped converters

2015· article· en· W1968541431 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Power Electronics · 2015
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsConvertersControl theory (sociology)WeightingModel predictive controlVoltageElectronic engineeringComputer scienceCapacitorEngineeringControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

This study proposes a generalised approach based on model predictive strategy for the current control, dc‐link capacitor voltages balancing, switching frequency reduction and common‐mode voltage mitigation in multilevel diode‐clamped converters. A generalised discrete‐time model of the converters is presented, where all the control objectives are formulated in terms of the switching states. The control goals are expressed as a cost function, and with the help of suitable weighting factors these goals are met simultaneously. The cost function minimisation is used as criteria for choosing the best switching state which would be applied to the converter during next sampling interval. The real‐time digital control issues such as computational burden and delay compensation are also discussed. The feasibility of the proposed method is verified by simulations in three‐ to six‐level converters, and by experiments in three‐ and four‐level converters.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
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 head0.010
GPT teacher head0.218
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