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Record W2119150235 · doi:10.1109/cca.2007.4389322

Robust Nonlinear Control of a Voltage-Controlled Magnetic Levitation System with Disturbance Observer

2007· article· en· W2119150235 on OpenAlexaff
Zi‐Jiang Yang, Hiroshi Tsubakihara, Shunshoku Kanae, Kiyoshi Wada, Chun‐Yi Su

Bibliographic record

Venue˜The œproceedings of the IEEE Conference on Control Applications/˜The œproceedings of the ... IEEE Conference on Control Applications · 2007
Typearticle
Languageen
FieldEngineering
TopicMagnetic Bearings and Levitation Dynamics
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)BacksteppingNonlinear systemMagnetic levitationRobust controlControl systemController (irrigation)Control engineeringState observerComputer scienceEngineeringAdaptive controlControl (management)MagnetPhysics

Abstract

fetched live from OpenAlex

This paper considers the control problem of a popular magnetic levitation system, which is open-loop unstable and strongly nonlinear associated with the electromechanical dynamics. The system dynamics is governed by a third-order nonlinear differential equation. The overall controller is designed through a backstepping manner by combining both the robust control and disturbance observer techniques. With the help of nonlinear damping terms, the input-to-state stability (ISS) property of the overall nonlinear control system is proved. Rigorous analysis of the ISS property is given, and experimental results are included to show the excellent position tracking performance of the designed control system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.206
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations15
Published2007
Admission routes1
Has abstractyes

Explore more

Same venue˜The œproceedings of the IEEE Conference on Control Applications/˜The œproceedings of the ... IEEE Conference on Control ApplicationsSame topicMagnetic Bearings and Levitation DynamicsFrench-language works237,207