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Record W2122396646 · doi:10.1109/isie.2007.4374663

A DSP based real-time simulation of Dual-Bridge Matrix Converters

2007· article· en· W2122396646 on OpenAlexaff
Mahmoud Hamouda, Farhat Fnaiech, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsBlock diagramDSPACEDigital signal processingComputer scienceMATLABExecutableBlock (permutation group theory)ConvertersController (irrigation)State spaceSoftwareSimulationEmbedded systemComputer hardwareEngineeringOperating systemAlgorithmElectrical engineering

Abstract

fetched live from OpenAlex

This paper investigates the state-space modeling and real-time simulation of dual-bridge matrix converters (DBMC) based on a DS1104 digital signal processor. This single board controller of dSPACE uses the matlab-simulink software as a front-end for the implementation of graphic models in block- diagram format. First, the state-space model of the converter and the SVM control system are designed with simulink in the form of user-friendly block-diagram. Next, C-codes are generated from the block diagrams with the real-time workshop. After that the executable code is automatically downloaded to the target DSP board. Finally, real-time simulation results are presented and compared to those obtained using off-line computer simulations. Good agreement is observed between both simulation results which shows the effectiveness and accuracy of the proposed realtime simulator.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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