Neural Filter Based Integrator for Virtual Flux Estimation in Direct Power Control of Three-Phase PWM Rectifiers
Bibliographic record
Abstract
In this paper, new neural filter (NF) based integrator (NF-I) is developed for virtual flux (VF) estimation in direct power control (DPC) of a three-phase pulse width modulation (PWM) rectifier. The main advantages of the proposed NF-I are its simple structure, accuracy and provides fast VF estimation compared to the traditional first order low-pass (FOLP) filter. The NF capability to online filtering distorted signals is exploited for extracting fundamental components of VF obtained from a pure integration. Numerical simulations of the proposed NF-I inserted in the VF based DPC (VF-DPC) are carried out under different grid voltage conditions. Steady state and dynamic performances of the NF-I are compared with those obtained with the traditional FOLP filter. Simulation results illustrate good performances of the NF-I inserted in the VF-DPC strategy.
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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".