The time delay effect in the predictive current controller of single-phase grid-connected power converter
Bibliographic record
Abstract
Predictive current controllers (PCCs) have demonstrated several advantages for applications in grid-connected power electronics converters (PECs). These advantages include fast, dynamic, and accurate response, along with stable digital implementations. However, existing implementations of PCCs suffer degraded performance due to the time-delay introduced by the system requirements. Understanding the time-delay effect is very important in order to improve the performance, stability, and robustness of the PCC. Unfortunately, the time-delay effect in the PCC has not been well studied in the existing literature. This paper presents detailed analysis of the PCC under time delay and provides a novel relationship between the time delay and the maximum accepted model mismatch ratio before the output current oscillates and fails to meet the standard power quality requirements. This work is verified experimentally on 12kW grid-connected single-phase PEC.
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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".