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Record W2146363281 · doi:10.1109/ccece.1996.548222

Robust performance analysis of a controlled synchronous machine

2002· article· en· W2146363281 on OpenAlexaff
Ouassima Akhrif, Lahcen Saydy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
Fundersnot available
KeywordsReactanceRobustness (evolution)Control theory (sociology)Transmission lineComputer scienceFault (geology)Robust controlController (irrigation)VoltageEngineeringControl (management)Control systemElectrical engineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

In this work we investigate the robust performance of a controller which was originally proposed by M. Araki et al. (see Eighth IFAC World Congress, Kyoto, Japan, p.3123-35, 1981) to control a synchronous machine connected to an infinite bus through a transmission line. The objectives of the design by Araki et. al. were to ensure (1) satisfactory voltage regulation in the pre-fault state and (2) satisfactory transient response in the post-fault state. The pre-fault and post-fault states are characterized by two extreme values of the line reactance X/sub e/, namely X/sub e1/=0.5 and X/sub e2/=0.8. However, as pointed out by Araki et. al., the controller is required to exhibit a satisfactory performance for a variety of operating conditions. In this article we analyze the robustness of the proposed controller for an uncertain value of the line reactance X/sub e/.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.178
Teacher spread0.165 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2002
Admission routes1
Has abstractyes

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