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Record W2154554989 · doi:10.1109/epec.2009.5420781

DSP-based sinusoidal PWM signal generation algorithm for three phase inverters

2009· article· en· W2154554989 on OpenAlexaff
Abdelrahaman Yousif Eshag Lesan, Mamadou Lamine Doumbia, Pierre Sicard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPulse-width modulationDigital signal processingInverterComputer scienceElectronic engineeringVoltageHarmonicThree-phaseControl theory (sociology)EngineeringElectrical engineeringControl (management)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Generation of DSP-based patterns to control voltage source inverters substantially helped the development of modern electric drives used in various applications. Although the DSP control is well known, there are few papers that cover in detail the control signal generation methodology. This paper presents a DSP-based algorithm to generate sinusoidal PWM signals. The sinusoidal PWM generation algorithm is written in C language so it can be reused easily, in addition to the flexibility it provides in terms of changing the PWM switching frequency and the fundamental frequency of the inverter output voltage. The algorithm development methodology and the experimental results are presented. The output voltage and current harmonic spectra are compared for 5 kHz and 10 kHz carrier frequencies. The results show the effectiveness of the proposed algorithm. This work is part of a research project that aims to develop sensorless vector control of induction machines. This part is presented separately to document DSP based PWM algorithm development process.

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 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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.804

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.249
Teacher spread0.220 · 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 teacher head, not a consensus.

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

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

Citations12
Published2009
Admission routes1
Has abstractyes

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