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Record W1569701991 · doi:10.1109/ccece.2015.7129433

Sliding mode speed control for wind energy conversion systems

2015· article· en· W1569701991 on OpenAlexaff
Adel Merabet, Khandker Tawfique Ahmed, Hussein Ibrahim, Rachid Beguenane, K. Belmokhtar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRoyal Military College of CanadaSaint Mary's University
Fundersnot available
KeywordsVariable speed wind turbineTurbineRobustness (evolution)Control theory (sociology)Wind speedWind powerSliding mode controlParametric statisticsComputer scienceGenerator (circuit theory)Control systemControl engineeringEngineeringPermanent magnet synchronous generatorControl (management)Power (physics)VoltageAerospace engineeringNonlinear systemElectrical engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

A sliding mode control strategy for speed tracking problem in variable speed wind turbine system is proposed in this paper. It is developed from the mechanical equation of the turbine-generator rotor. The validation of the proposed control is done using OPAL-RT real-time simulator and electrical modules from Lab-Volt. The proposed control strategy provides robustness to the parametric uncertainties of the wind turbine and generator.

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 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 score0.972
Threshold uncertainty score0.447

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2015
Admission routes1
Has abstractyes

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