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Record W2042169926 · doi:10.1002/rnc.634

Linear QFT control of a highly nonlinear multi‐machine power system

2001· article· en· W2042169926 on OpenAlex
Matei Kelemen, Ouassima Akhrif

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

VenueInternational Journal of Robust and Nonlinear Control · 2001
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)GovernorNonlinear systemElectric power systemOperating pointPower (physics)Rotor (electric)Control engineeringController (irrigation)Voltage regulatorComputer scienceEngineeringVoltageControl (management)Electronic engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract A quantitative feedback theory (QFT) method of Horowitz, treating nonlinearities as equivalent disturbances, is applied to the linear control of a multi‐machine power system. This system has a smooth nonlinear dynamics so the original approach was simplified. From the design point of view good results were obtained with simple controllers (automatic voltage regulator, speed governor, power system stabilizer) when the power system was affected by large load variations and short circuits. To reduce significantly the steady state errors which appeared, a novel rotor speed error amplification scheme was employed. This increased the autonomy of the controlled power system to combat big distortions from normal operating conditions. Copyright © 2001 John Wiley & Sons, Ltd.

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)0.001
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 score0.887
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.225
Teacher spread0.217 · 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