Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor
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Bibliographic record
Abstract
This paper presents a cascaded nonlinear predictive control of a permanent magnet synchronous motor (PMSM) drive. The Taylor series expansion is used to carry out the prediction defined on a finite horizon. However, it's well-known that this control strategy cannot remove completely the steady state error under mismatched parameters and load torque. Then, the full knowledge of machine parameters and operating conditions must be used to compute the control law. For that reason, a disturbance observer is designed for the estimation of the offset caused by the parameters uncertainties and external disturbance. By taking into account the offset observer in the global control system design, an equivalent cascaded proportional integration (PI) action is obtained. The performances of the proposed control strategy are analysed by simulation. The obtained results show the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection.
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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