Virtual-Flux Finite Control Set Model Predictive Control of Dual-Three Phase IPMSM Drives
Bibliographic record
Abstract
In this paper, a virtual-flux finite control set model predictive control (MPC) strategy for dual three-phase interior permanent magnet synchronous motors (DTP-IPMSM) is proposed. The technique is based on the conventional predictive current control, but it maps the measured variables into a virtual- flux domain, thus simplifying the prediction stage. The technique uses a flux-based cost function to track the estimated reference flux. The flux tracking cancels out to guarantee an improved current tracking, and thus, a better torque ripple. The proposed technique is validated through simulation of a 100 kW DTP- IPMSM in Matlab/Simulink. Results evidenced a reduced current control error, thus improving the torque tracking up to 38.9 % when compared to the conventional inductance based model predictive control.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".