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Record W2091265492 · doi:10.1109/isie.2006.295600

DSP Speed Control of Single-Phase Induction Motor Using C Programming

2006· article· en· W2091265492 on OpenAlex
Langdon Guay, John Salmon

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDigital signal processingInduction motorComputer scienceElectronic speed controlOpen-loop controllerControl systemDigital signal processorMachine controlLimit (mathematics)Computer hardwareControl engineeringEngineeringElectrical engineeringMathematicsClosed loop

Abstract

fetched live from OpenAlex

Use of a high-speed DSP to provide speed-control of a single-phase induction motor is covered in this paper. DSP programming is performed in C rather than assembly language to illustrate the usefulness of a high-level language in such applications. Use of C programming produces direct-control of DSP hardware while allowing simpler programming than assembly language and reducing development time. Algorithms and system configuration are chosen to limit the complexity, cost and development-time for the system. Previously-programmed C-language inline functions are used to produce open-loop V/F speed-control of the single-phase induction motor or SPIM. Necessary modifications that allow open-loop V/f control of single-phase induction motors are examined. The modified open-loop V/F control for single-phase motors is adjusted experimentally to produce the optimum speed-control of a split-phase SPIM. Experimental results are provided for the entire system so the degree of success for such a control methodology can be evaluated

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.646

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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

Quick stats

Citations4
Published2006
Admission routes1
Has abstractyes

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