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Record W2128533762 · doi:10.1109/tcst.2007.908213

Adaptive Reshaping of Excitation Currents for Accurate Torque Control of Brushless Motors

2008· article· en· W2128533762 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsControl theory (sociology)Direct torque controlTorqueTorque motorController (irrigation)Stall torqueAdaptive controlDC motorSynchronous motorComputer scienceAC motorControl engineeringEngineeringVoltageInduction motorPhysicsControl (management)Artificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Accurate torque control of a brushless motor requires the motor's torque characteristics, which follows a periodic function of motor angle. This brief presents a direct adaptive controller for torque control of brushless motors, which estimates the Fourier coefficients of this periodic function based on the measurements of motor phase voltage and angle. It will be analytically shown that the proposed adaptive controller achieves torque tracking regardless of the trajectories of input signals. Moreover, the adaptive controller does not rely on the modeling of the mechanical load, so that control implementation is simple and modular. Experimental results obtained from the McGill/MIT motor have demonstrated that motor torque converges to the command torque.

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 categoriesMeta-epidemiology (narrow)
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 score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.231
Teacher spread0.209 · 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