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Record W2334342870 · doi:10.3166/jesa.46.453-478

Méthodes de synthèse de correcteurs robustes d’ordre réduit pour les boucles de stabilisation inertielle de Ligne de Visée

2012· preprint· fr· W2334342870 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2012
Typepreprint
Languagefr
FieldEngineering
TopicIterative Learning Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Afin d'assurer un haut degré de performance en précision de pointage tout en étant robustes aux variations du système, les correcteurs des boucles de stabilisation inertielle de Ligne de Visée ont une structure particulière imposée par la nature des perturbations à rejeter. La synthèse H∞ par Loop Shaping est une technique bien adaptée à cette problématique mais elle aboutit à des correcteurs d'ordre élevé compte tenu de l'ordre du modèle de synthèse et des pondérations nécessaires à la traduction des objectifs de synthèse. La maîtrise de l'ordre des correcteurs est alors abordée à travers la synthèse H∞ à ordre fixé, tout d'abord via une approche par factorisations premières et optimisation LMI, puis par les outils récents procédant par optimisation non lisse qui permet d'élargir le cadre de la première approche.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
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 score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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