Solutions to avoid the worst case scenario in driving systems working under continuously variable conditions
Why this work is in the frame
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Bibliographic record
Abstract
The paper presents a study on the behavior of some control solutions for electric drive systems evolving in conditions of reference, disturbance and parameter variability. The results of this study substantiate new control solutions that ensure the possibility to avoid the worst cases. The study addresses the real situation of an electric drive system with continuously variable reference input (speed), variable moment of inertia and variable load disturbance. Two control structures with controllers with fixed parameters are considered and discussed with focus on the speed control loop. The justified new control structures employ the switching between several control algorithms; their design is based on the detailed mathematical model of the plant and on the particular features of the drive system. The solutions are validated by means of digital simulations and experiments on a laboratory equipment application for three values of the moment of inertia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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