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Record W1976460640 · doi:10.1109/whc.2013.6548494

Stability analysis of delayed 4-channel bilateral teleoperation systems

2013· article· en· W1976460640 on OpenAlexaff
Noushin Miandashti, Mahdi Tavakoli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTeleoperationPassivityControl theory (sociology)Stability (learning theory)Channel (broadcasting)MicrocontrollerTransfer functionMaster/slaveControl systemTeleroboticsComputer scienceEngineeringControl engineeringControl (management)RobotEmbedded systemMobile robotArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

This paper studies the stability of a delayed 4-channel bilateral teleoperation system based on the passivity framework. Assuming that the operator and the environment are passive systems, the stability of the teleoperation system is reduced to ensuring the passivity of a master control unit (MCU), a slave control unit (SCU), and the time-delayed communication channel. Each of these three blocks is modeled as a 2 × 2 transfer function matrix and passified using our proposed approach in a multi-loop feedback (MLF) structure. We report conditions on the controllers of the 4-channel architecture that are sufficient for passivity of MCU and SCU. Simulation results confirm the validity of these conditions for the stability of the teleoperation 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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.197
Teacher spread0.184 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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