Carrier-Based MPC for Interleaved 2L-VSIs with Reduced Low-order Zero-Sequence Circulating Current
Bibliographic record
Abstract
In this paper, a carrier-based model predictive control (CB-MPC) algorithm is proposed to regulate power sharing of paralleled two-level voltage-sourced inverters (2L-VSIs). Carriers are adopted in the proposed controller to enable interleaving. The proposed controller can be implemented in either distributed or centralized manner, depending on the application circumstances. The distributed CB-MPC is more suitable for large modular parallel inverter systems where communication lines are prohibited. On the other hand, the low-order zero-sequence circulating current (ZSCC) can be fully eliminated with proposed centralized CB-MPC, when communications become available among a small number of paralleled inverter modules. With either scheme, multiple goals can be achieved including fast dynamic response, carrier interleaving, fixed switching frequency, ZSCC elimination, and reduced computational burden; which makes the proposed method a practical MPC solution for various industrial applications. Effectiveness of the proposed CB-MPC has been verified by simulation and experimental results.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".