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Record W4411232151 · doi:10.1109/jas.2024.125037

Adaptive Sliding Mode Control with Linear Extended State Observer for Active Magnetic Bearing-Rotor Systems

2025· article· en· W4411232151 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

VenueIEEE/CAA Journal of Automatica Sinica · 2025
Typearticle
Languageen
FieldEngineering
TopicMagnetic Bearings and Levitation Dynamics
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersNational Natural Science Foundation of China
KeywordsMagnetic bearingControl theory (sociology)State observerRotor (electric)Observer (physics)Sliding mode controlBearing (navigation)State (computer science)Mode (computer interface)Computer sciencePhysicsControl (management)EngineeringNonlinear systemMechanical engineeringArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

Dear Editor, Active magnetic bearings (AMBs) are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations. This paper proposes an active levitation control algorithm based on adaptive sliding mode control (ASMC) equipped with linear extended state observer (LESO). Sufficient conditions are derived to guarantee the asymptotical stability of the associated closed-loop system. Experiments are conducted on a real AMB-rotor platform to demonstrate the effectiveness and superiority of the proposed algorithm.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.482
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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