Digital Control of a Shunt Hybrid Power Filter Adopting a Nonlinear Control Approach
Bibliographic record
Abstract
This paper proposes a nonlinear derivative-less control approach for controlling a three-phase shunt hybrid power filter (SHPF). The dynamic model of the SHPF system is first elaborated in the stationary frame and then transformed into a “dq” reference frame. The control system is divided into two separate loops, namely the two current dynamics inner loop and the dc voltage dynamic outer loop. The exact feedback linearization technique is used to decouple the inner loop variables. Proportional-integral controllers are utilized to control the SHPF input currents and dc-bus voltage. The proposed nonlinear control is first simulated and then validated on a 2.5-kVA laboratory prototype supported by the DS 1104 digital real-time controller board of dSPACE. Satisfactory results, such as low-ac-current total harmonic distortion, fast step response, and high robustness under load variation, are obtained. Significantly high correlation between the experimental results and the theoretical model, implemented with SIMULINK/Matlab, is obtained.
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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 | 0.000 |
| 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) | 0.001 | 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".