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Record W4225664253 · doi:10.1109/tpel.2022.3157267

Efficient Modeling and Systematic Design of Enhanced Phase-Locked Loop Structures

2022· article· en· W4225664253 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

VenueIEEE Transactions on Power Electronics · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of AlbertaPolytechnique Montréal
Fundersnot available
KeywordsComputer sciencePhase-locked loopLoop (graph theory)GridPhase (matter)Control engineeringControl theory (sociology)EngineeringArtificial intelligenceMathematicsControl (management)PhysicsJitter

Abstract

fetched live from OpenAlex

This article presents approaches for efficient modeling and systematic design of enhanced phase-locked loop (ePLL) structures. While different ePLL structures have found a wide acceptance for various applications, their modeling and design aspects have not been fully and systematically reported in the existing literature. This article fills this gap by presenting an effective modeling approach for both the single- and three-phase ePLLs. The models are derived with a view to minimize the number of parameters to be adjusted to simplify the design. The models are then used to develop systematic design algorithms for their parameters. As an example, application of the ePLL in a grid-connected inverter is formulated and studied through simulation and experimental results. The design and simulation files are made available.

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 categoriesnone
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 score0.909
Threshold uncertainty score0.556

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 head0.006
GPT teacher head0.204
Teacher spread0.197 · 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