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Record W2374615029

Control of Bi-Directional DC Converter in DC Micro Network

2014· article· en· W2374615029 on OpenAlexaff
Liu Xiao-don

Bibliographic record

VenueJournal of Power Supply · 2014
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsQueen's University
Fundersnot available
KeywordsControl theory (sociology)Feedback linearizationMATLABController (irrigation)LinearizationCapacitorVoltageSliding mode controlEngineeringComputer scienceControl (management)Nonlinear systemElectrical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Adaptive control was combined with sliding mode control based on exact feedback linearization, which was applied to the bi-directional DC/DC converter in this paper, whose parameters were corrected in real time with change of super capacitor voltages and loads. The non-minimum phase characteristics and variable structure features of the converter were solved, and the system errors were reduced and the system response speed was improved. Therefore,the proposed strategy made the ultra-capacitor play a better role on stabling bus voltage in DC micro-network. The converter state equation was proposed, and the accurate feedback linearization model through coordinate transformation was deduced and the adaptive sliding mode controller was designed on this base. Finally, the results of simulation built by Matlab/Simulink software show that the controller with the adaptive control has a better effect than the one without introducing adaptive control.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0000.000
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 head0.004
GPT teacher head0.199
Teacher spread0.195 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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