Design of a Robust Speed and Position Sensorless Decoupled P-Q Controlled Doubly-Fed Induction Generator for Variable-Speed Wind Energy Applications
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Bibliographic record
Abstract
This paper proposes an implementation of a decoupled P-Q control of a DFIG that does not rely on mechanical sensors and a speed and position sensorless algorithm that is robust to variations of the values of the machine parameters. In this paper, the sensorless control is based on a modified phase-locked loop with an improved positioning algorithm. This eliminates the need to estimate the speed based on the machine parameters, which results in a significant improvement in speed control robustness to parameter variations. In addition, the algorithm avoids using differentiation which can lead to significant inaccuracy due to the noise inherent in measured signals. Theoretical and simulation results were validated on an experimental setup, using a laboratory 5 hp DFIG.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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