Online multi‐parameter estimation of interior permanent magnet motor drives with finite control set model predictive control
Why this work is in the frame
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Bibliographic record
Abstract
This study presents an online multiparameter estimation scheme for interior permanent magnet motor drives that exploits the switching ripple of finite control set (FCS) model predictive control (MPC). The combinations consist of two, three, and four parameters are analysed for observability at different operating states. Most of the combinations are rank deficient without persistent excitation (PE) of the system, e.g. by signal injection. This study shows that high frequency current ripples by MPC with FCS are sufficient to create PE in the system. This study also analyses parameter coupling in estimation that results in wrong convergence and propose a decoupling technique. The observability conditions for all the combinations are experimentally validated. Finally, a full parameter estimation along with the decoupling technique is tested at different operating conditions.
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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 | 0.000 |
| 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