Sur la commande tolérante aux défauts des machines asynchrones. Une approche implicite
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.
Bibliographic record
Abstract
Dans cet article, deux approches de commande tolérante aux défauts (FTC Fault-Tolerant Control) sont étudiées et appliquées à la machine asynchrone.Dans ce contexte, la phase de détection et d'isolation du défaut est décalée par rapport à la phase de reconfiguration de la commande.Celle-ci est réalisée en testant l'état d'un modèle interne qui s'active automatiquement dès l'apparition d'un défaut pour compenser son effet.Cet effet peut être convenablement modélisé par un signal exogène issu d'un système autonome stable appelé exosystème.Une commande additive est ainsi ajoutée à la commande nominale.Issue du modèle interne, cette commande sert à compenser l'effet du défaut.La première approche FTC exploite un modèle interne basé sur l'équation de Sylvester qui entraîne une divergence lorsque la machine est affectée par deux défaut ou plus.La seconde approche, quant à elle, élimine le problème de divergence par un réglage adapté des matrices du système.ABSTRACT.This paper deals with the application of implicit fault-tolerant control techniques to induction motor drives using a Backstepping approach.For that purpose, the induction motor, the disturbances as well as the faults signals have been modeled.A Backstepping control strategy (nominal control) is then synthesized and applied to the induction motor drive for robust control purposes.For fault-tolerant control purposes, an additive control term is generated from an internal state model in order to compensate for the fault effects.Simulations carried-out on a 1.1-kW induction motor drive clearly show the effectiveness of the proposed approaches.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it