Modelling and control of a boost converter for irregular input sources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it