Improved Finite Control Set Model Predictive Control for Permanent Magnet Synchronous Motor Drives with Current Ripple Minimization
Bibliographic record
Abstract
Finite Control Set Model Predictive Control (FCSMPC) is widely recognized as a simple and effective control strategy for electric motor drives. It achieves quick dynamic response but suffers from large current ripples and unsatisfied steady-state performance. By introducing the concept of duty cycle, the steady-state performance gets improved but still results in large current ripples, especially under higher rotor speed. This paper proposes an improved FCSMPC which combines the concept of duty cycle and virtual voltage vectors. It applies optimal virtual voltage vector at every sampling interval that reduces the current ripples by successfully eliminating the error between the reference value and the actual value of the current. The optimal virtual voltage vector is realized by at most two suboptimal active voltage vectors and one null voltage vector in proper duty cycle ratios. The outstanding performance of the proposed method is validated by experiment for an interior permanent magnet synchronous machine.
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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) | 0.000 | 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 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".