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Record W2129600290 · doi:10.1109/pesc.2004.1355085

Adaptive backstepping based nonlinear control of an IPMSM drive

2004· article· en· W2129600290 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.

Bibliographic record

Venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551) · 2004
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsLakehead University
Fundersnot available
KeywordsBacksteppingControl theory (sociology)Controller (irrigation)Lyapunov stabilityNonlinear systemMATLABComputer scienceElectronic speed controlControl engineeringLyapunov functionAdaptive controlStability (learning theory)Scheme (mathematics)EngineeringControl (management)Mathematics

Abstract

fetched live from OpenAlex

This paper investigates the performance of a novel speed control scheme for an interior permanent magnet synchronous motor (IPMSM) based on a newly developed nonlinear adaptive control scheme. The system model equations provide the basis for the controller which is designed using adaptive backstepping technique. Using Lyapunov's stability theory, it is also proved that the control variables are asymptotically stable. The complete system model is developed and then simulated using MATLAB/Simulink software. Performance of the proposed controller is investigated extensively at different dynamic operating conditions such as sudden load change, command speed change and parameter variations. The results show the global stability of the proposed controller end hence found to be suitable for high performance industrial drive applications.

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)0.001
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: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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