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Record W2989769854 · doi:10.1109/ias.2019.8911986

Small Signal Analysis and Closed-Loop Design of Constant Frequency Operated Snubberless Naturally-Clamped Soft-Switching Current-Fed Push-Pull DC/DC Converter

2019· article· en· W2989769854 on OpenAlexaff
Koyelia Khatun, Akhil Raj Kizhakkan, Venkata R. Vakacharla, Akshay Kumar Rathore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)SnubberSIGNAL (programming language)Controller (irrigation)Small-signal modelCurrent (fluid)Loop (graph theory)Computer scienceEngineeringMathematicsControl (management)CapacitorElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a detailed small signal analysis and closed loop controller design of snubber less naturally-clamped soft-switching bidirectional current-fed push-pull dc/dc converter. Small-signal model is developed through state-space approach and a two-loop control is proposed to stabilize the system. Ability of designed controller to maintain stability in system against load disturbances are validated using PSIM 11.1.5 platform and obtained results are included in this paper to validate the design procedure.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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 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

Citations4
Published2019
Admission routes1
Has abstractyes

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