Control of a high‐voltage bidirectional dc–dc flyback converter for driving DEAs
Bibliographic record
Abstract
This study presents modelling and control of a high‐voltage ratio flyback converter for driving capacitive loads including smart material dielectric elastomer actuators (DEAs). These actuators find various applications including artificial muscles, optical devices, smart skin, and acoustics but require high actuation voltages. To this end, a high‐voltage bidirectional flyback converter for driving a capacitive load is studied in terms of modelling and control and applied to a DEA. The state‐space model of the converter is obtained for the capacitor charge and discharge modes when the converter operates in the continuous conduction mode and used to obtain a load voltage controller using the feedback linearisation method. The converter can be used to regenerate the capacitor charge into the dc source. The proposed hardware and control strategy was built and validated by driving DEA capacitive loads operating at high voltages around 4 kV. The experimental results are presented which validate the performance of the proposed converter and its control strategy.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".