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Record W2155598967 · doi:10.1109/robot.2008.4543281

A New Robust Stability Analysis and Design Tool for Bilateral Teleoperation Control Systems

2008· article· en· W2155598967 on OpenAlexaff
Amir Haddadi, Keyvan Hashtrudi-Zaad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsTeleoperationControl theory (sociology)Stability (learning theory)Robust controlOperator (biology)Computer scienceInstabilityStability conditionsStability criterionControl systemControl engineeringControl (management)EngineeringMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a powerful robust stability analysis technique is introduced and developed for teleoperation systems. The methodology is based on wave parameters and discusses absolute stability and potential instability using scattering and is originally used in microwave systems [1]. The proposed method provides suitable mathematical and visual aids to determine bounds or regions of passive environment impedances for which a potentially unstable system connected to any passive operator is stable, and vice-versa. Furthermore, a novel stability parameter is proposed to maximize the derivation of the above bounds or regions. This results in less conservative guaranteed stability conditions compared to the Llewellyn’s criterion; thus, achieving a better compromise between stability and performance. The proposed methodology allows for the design of bilateral control systems when such bounds are known or even when the operator or environment dynamics are active. The new robust stability analysis and Llewellyn’s criterion are numerically evaluated and compared with each other on two common teleoperation control architectures.

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)0.002
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.033
GPT teacher head0.206
Teacher spread0.172 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

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