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Record W2033467622 · doi:10.1109/tro.2013.2295889

Analysis of Coupled Stability in Multilateral Dual-User Teleoperation Systems

2014· article· en· W2033467622 on OpenAlexaff
Kamran Razi, Keyvan Hashtrudi-Zaad

Bibliographic record

VenueIEEE Transactions on Robotics · 2014
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsTeleoperationControl theory (sociology)ImmittanceStability (learning theory)Dual (grammatical number)Computer scienceExponential stabilityController (irrigation)ControllabilityControl engineeringEngineeringMathematicsControl (management)Nonlinear systemArtificial intelligenceApplied mathematics

Abstract

fetched live from OpenAlex

In this paper, we set out a framework for the analysis of coupled stability in dual-user linear teleoperation systems. An extension of the Zeheb-Walach (ZW) criteria for absolute stability of an n-port network will be stated and proven. While the original theorem states conditions for asymptotic stability of a network terminated by passive impedances, the extended version allows for poles on the imaginary axis, which makes it applicable to a larger class of systems, such as robotic applications with position feedback. The extended theorem includes conditions on the Laurent expansion of the elements and the principal minors of the network immittance matrix. A novel dual-user shared control paradigm, realizing a three-way gearbox mechanism, is presented. A numerical analysis of absolute stability of the three-port network, representing the shared control architecture, demonstrates the effectiveness of the extended Zeheb-Walach method.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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

Citations39
Published2014
Admission routes1
Has abstractyes

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