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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 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 score0.856
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.033
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 teacher head, 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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