Robust Control Strategy Design for Single-Phase Grid-Connected Converters Under System Perturbations
Bibliographic record
Abstract
In single-phase grid-connected converters, unexpected perturbations and variations of system parameters can deteriorate the performance of grid current and dc-link voltage control and even jeopardize the stability and operation of loads. In this paper, a robust control strategy for the single-phase grid-connected converter operating under multiple system perturbations is proposed. An adaptive quasi-proportional-resonant (AQ-PR) controller for the grid current is adopted in combination with an equivalent inductance identification algorithm, which assures that the parameters of the AQ-PR controller can be online calibrated to attain accurate current regulation under ac-side inductance uncertainties. A super-twisting sliding mode (ST-SM) controller for the dc-link voltage is proposed to enhance system behavior under both internal and external disturbances. The convergence of the controller is ensured by utilizing Lyapunov theory. Experimental prototype and rigorous tests are presented to validate the feasibility and robustness of the proposed approach under various perturbations.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".