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Record W4391707571 · doi:10.1109/tla.2024.10431419

Fractional-Order Control for Voltage Regulation in Bidirectional Converters: An Experimental Study

2024· article· en· W4391707571 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Latin America Transactions · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConvertersVoltageVoltage regulationControl theory (sociology)Order (exchange)Control (management)Computer scienceElectronic engineeringEngineeringElectrical engineeringEconomicsFinance

Abstract

fetched live from OpenAlex

The theoretical application of fractional equations in controller development is not a new topic. The first efforts on this topic were reported in the late 1970s. However, in the last four years, a greater number of papers related to fractional control have been published than the one accumulated in previous years. Motivated by the above, this paper reports the step-by-step development of this type of control in a bidirectional converter. Furthermore, the discrete-time equivalent of the developed fractional control is implemented on Texas Instruments F280042C digital signal processor. The experimental results of the discrete fractional compensator are compared with the experimental results of a conventional proportional integral derivative (PID) controller. The results show a notable improvement in the response of the bidirectional converter with the fractional control; specifically, faster responses and less overshoot in most of the experiments carried out. Also, the existing challenges facing the widespread application of this control technique are notorious and are extensively addressed in this article.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.272
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it