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Record W2159544141 · doi:10.1109/icsmc.1995.538017

Position and force control of an electrohydraulic manipulator in the presence of friction

2002· article· en· W2159544141 on OpenAlexaff
Shahram Tafazoli, C.W. de Silva, P.D. Lawrence

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsControl theory (sociology)TrajectoryPosition (finance)AccelerationController (irrigation)Work (physics)Computer scienceTracking (education)Control engineeringEngineeringControl (management)Mechanical engineeringPhysicsArtificial intelligenceClassical mechanics

Abstract

fetched live from OpenAlex

A work cell for decapitation of salmon has been developed in the authors' Industrial Automation Laboratory. An X-Y electrohydraulic manipulator is used to quickly move a sharp blade to its desired position in the horizontal plane. This blade slides on two lubricated metal guideways. Precise, fast and smooth positioning of the blade is considered here. A quintic polynomial approach is used to generate a smooth reference trajectory. A novel friction-compensating control strategy is proposed to improve tracking performance of the manipulator. The approach is based on an acceleration feedback control law. According to the experimental results, this controller outperforms the classical PD (Proportional+Derivative) controller. In the force control domain, it is experimentally verified that force control is possible as long as no motion is involved. In other words, the reference force is below the static friction break-away force. PD control is used for this purpose. This type of force control can be used to compensate for disturbance force before it actually affects movement of the manipulator.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.126

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 head0.009
GPT teacher head0.193
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 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

Citations5
Published2002
Admission routes1
Has abstractyes

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