Finite Control Set Model Predictive Control of an Active Nested Neutral-Point-Clamped Converter
Bibliographic record
Abstract
The flying capacitors (FCs) of the nested neutral-point-clamped (NNPC) converter show an inherent voltage ripple at the fundamental frequency. This ripple can be significantly large under some operating conditions of the converter and hence can affect the performance. In this paper, a modified NNPC is proposed, so called active NNPC (ANNPC) converter. Like other multilevel converters, ANNPC also required capacitor voltage balancing, therefore finite control set model predictive control (FCS-MPC) scheme is proposed to control such objective. A mathematical model is developed to be used in the FCS-MPC. The performance of the ANNPC is compared with the NNPC in terms of capacitor voltage ripples and the total harmonics distortion of the output voltage and current. The results are validated by simulations.
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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 | 0.001 |
| 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".