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Record W2105785760 · doi:10.1109/tcst.2012.2205386

Bilateral Control of Nonlinear Pneumatic Teleoperation System With Solenoid Valves

2012· article· en· W2105785760 on OpenAlexaff
Quyen Minh Le, Minh Tu Pham, Mahdi Tavakoli, Richard Moreau, Jean-Pierre Simon, Tanneguy Redarce

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTeleoperationPneumatic actuatorControl theory (sociology)ActuatorPneumatic flow controlSolenoidNonlinear systemControl valvesControl engineeringEngineeringControl systemComputer scienceControl (management)Mechanical engineering

Abstract

fetched live from OpenAlex

In past research on the control of pneumatic actuators, typically proportional servovalves have been used for achieving high-performance control of the mass flow rate. In this brief, we instead use fast-switching ON/OFF valves due to their distinct advantages in terms of low cost and small size. Accurate control of pneumatic actuators with ON/OFF solenoid valves is a challenge since the system dynamics is both discrete input and highly nonlinear. In this brief, we apply a hybrid control algorithm to a pneumatic actuator with ON/OFF valves. Such a control approach is developed for choosing the best control vector at each sample time to track the reference state (i.e., desired force) in the inner force control loop within a bilateral teleoperation system. Experimental results show that good teleoperation transparency is achieved despite all the obstacles such as discrete input and nonlinear behavior of the pneumatic-actuated 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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