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Record W2108258399 · doi:10.1109/tie.2011.2138670

High-Efficiency Line Conditioners With Enhanced Performance for Operation With Non-Linear Loads

2011· article· en· W2108258399 on OpenAlexaff
Thiago Batista Soeiro, Clóvis Antônio Petry, Luiz A. C. Lopes, Adriano Perín

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)InductanceAir conditioningTransfer functionBandwidth (computing)EngineeringVoltageController (irrigation)Electronic engineeringComputer scienceElectrical engineeringControl (management)Mechanical engineering

Abstract

fetched live from OpenAlex

This paper presents the analysis, design, and experimental performance verification of a serial type line conditioner. Since it processes only a fraction of the load power, the overall converter losses tend to be lower and the efficiency of the conditioner higher. Regarding the dynamic performance, the line inductance, which results in a positive zero in the transfer function of the plant, is taken into consideration when designing a voltage controller with higher bandwidth for faster response. In addition, a virtual resistance is included in the control of the system to damp oscillations often seen for operations at light load and with nonlinear load conditions. Experimental results obtained with a 10 kVA prototype of a serial line conditioner fed from the load side and the proposed feedback control scheme are presented to demonstrate the superior performance of the line conditioner.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.214
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 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
GenreMethods

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

Citations6
Published2011
Admission routes1
Has abstractyes

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