Modelling and control of a boost converter for irregular input sources
Bibliographic record
Abstract
In this study, the authors present the analysis and development of a boost-type switching converter for efficient power conversion from a source with an arbitrary low-frequency voltage waveform to a DC storage medium such as a battery. This type of energy transfer is of great interest in energy conversion systems involving low-frequency, time-varying input sources such as vibration energy harvesting and marine wave energy conversion. Motivated by these applications, a modelling and feedback control scheme is developed for a pulse-width-modulated (PWM) boost converter. In particular, conditions under which the converter would act as a ‘pseudo-resistor’ as seen by an arbitrary input voltage source are derived. Based on the pseudo-resistive relationship obtained between the input voltage and current, a feedback controller is developed that regulates the input resistance of the converter to a desired value; hence allowing purely active power conversion of an arbitrary band-limited input voltage source to a DC load. Numerical simulations and experimental results are presented that evaluate performance of the proposed modelling and feedback control scheme. An application involving energy conversion for a mechanical vibration system to act as a regenerative damper is considered.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".