Model Predictive Current Control of a 4-Level Negev Rectifier
Bibliographic record
Abstract
In this paper, the design and implementation of a model predictive current controller for a nested (T-Type) 4-level Negev rectifier is presented. This power converter is a modification of the Vienna rectifier that allows the generation of three partial DC link voltages, while maintaining a unity power factor at the utility grid side. This topology is intended to be a grid interface for supplying partial DC voltages to multilevel inverters, eliminating the need of voltage balancing control in the inverter’s side. The mathematical model of this converter is also presented and based on it, the model predictive controller is developed. To evaluate/compare the controller’s performance, a time division multiplexed on-off controller is also implemented in MATLAB/Simulink. Simulation results show the performance of both control strategies considering different operating conditions, in which, the proposed controller produces better total harmonic distortion levels in grid currents and voltage ripple in partial DC voltages.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".