Conception d'une loi de commande robuste de la pression dans un réservoir pneumatique à l'aide d'une formulation IML
Bibliographic record
Abstract
Ce mémoire présente une méthodologie d'élaboration d'une loi de commande proportionnelle-intégrale (PI) permettant la stabilisation robuste de la pression dans un réservoir pneumatique. L'idée principale est de convertir les non linéarités et les incertitudes du systèmes en un certains nombres de contraintes qui seront traités par le formalisme des inégalités matricielles linéaires (IML) en introduisant un ensemble d'équations généralisée de Lyapunov pour chaque contrainte. Ceci permet de contraindre les pôles du système dans une région prescrite du plan complexe selon les exigences désirées (temps de réponse, dépassement et mode du système en haute fréquence). La solution de ce problème d'optimisation convexe peut facilement être obtenue grâce à des algorithmes numériques implantés dans des logiciels de calcul tels que MATLAB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".