Open-loop speed estimators design for online induction machine synchronous speed tracking
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
Open-loop speed estimators (OLSE) and closed loop speed estimators (observers) based on flux estimation are usually inaccurate since they depend on ill-known induction machine (IM) parameters such as stator winding resistance. This paper presents two methods to track accurately the IM synchronous speed over a large speed range with OLSE. An accurate adaptive integration algorithm (AAIA) developed for quasi exact flux position and magnitude estimation over a wide speed range is used. A current based speed estimator using AAIA, which is completely independent of the IM parameters, is introduced. The accuracy of two OLSE designs was tested on a fixed frequency network and with indirect rotor flux oriented control (IRFOC) of a squirrel cage IM. These techniques were simulated on a commercial package and tested experimentally on a 1/2 HP IM and on a 3 HP IM
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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