Disturbance Estimator-Based Predictive Current Controller for Single-Phase Interconnected PV Systems
Bibliographic record
Abstract
A digital predictive current controller for a single-phase grid-side power electronics converter employed in photovoltaic (PV) systems is presented in this paper. A disturbance estimator is employed with the controller in order to minimize its sensitivity to any parameter variation, as well as to reject grid-side disturbances. The design of the controller and the estimator are carried out using the pole placement method. The performance of the developed current controller was tested and verified experimentally using a 5.4-kW grid-connected PV system. These experiments are carried out for different levels of power delivered to the grid under different variation in the system parameters. In addition, other controllers used for interconnected PV systems are also tested to highlight the advantages of the developed current controller. The testing results illustrate the capability of the developed current controller to provide accurate, fast, and robust responses with negligible sensitivity to parameters variations and disturbances on the grid side.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".