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Record W2013457647 · doi:10.1260/030952406778606232

Fuzzy Logic Based Vector Control of a Doubly-Fed Induction Generator in Wind Power Application

2006· article· en· W2013457647 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

VenueWind Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsControl theory (sociology)PID controllerWind powerInduction generatorFuzzy logicVector controlVariable speed wind turbineController (irrigation)TurbineFuzzy control systemComputer scienceEngineeringControl engineeringPower (physics)Generator (circuit theory)Induction motorVoltagePhysicsTemperature controlControl (management)

Abstract

fetched live from OpenAlex

In this article, a fuzzy PI gain scheduler for a vector controller is developed to control a doubly-fed induction generator used in a variable speed wind turbine. Effects of both main flux and leakage flux saturation are considered in the machine model in order to obtain more realistic results. Extensive simulations have been carried out on the proposed system to investigate its dynamic performance. A comparison between the developed vector controller with the proposed fuzzy PI gain scheduler and the same vector controller with a conventional PI controller employing fixed gains shows that using the fuzzy PI gain scheduler, the system has better performance and faster dynamic response without any steady-state error.

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: Empirical
Teacher disagreement score0.272
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 head0.005
GPT teacher head0.171
Teacher spread0.167 · 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