A Robust Vector Current Controller with Negative-Sequence Current Capability for Grid-Connected Inverters
Bibliographic record
Abstract
This paper presents a vector current controller (in the synchronous reference, or the dq, frame) with negative-sequence current injection capability for three-phase grid-connected converters. This capability is desired for the operation of the converter during unbalanced conditions and also for a certain type of islanding detection. The proposed controller first determines the double-frequency current references and then uses a sixth-order two-input two-output proportional-integral-resonance (PIR) structure, which is optimally designed. Compared with the existing similar approaches, the proposed controller has a simpler structure and more robust performance, e.g., against system parameter uncertainties and weak grid conditions. The proposed controller is developed for converters with both the L-type and LCL-type filters. For the LCL-type converter, a suboptimal partial state feedback control is also proposed to achieve robust stability and active damping of resonance poles without requiring additional sensors. Detailed experimental results are presented to illustrate the properties and performances of the proposed controller.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".