MétaCan
Menu
Back to cohort
Record W2108226380 · doi:10.1109/cdc.1991.261627

Acceleration feedback for flexible joint robots

2002· article· en· W2108226380 on OpenAlexaff
Mark C. Readman, Pierre Bélanger

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsRevolute jointControl theory (sociology)AccelerationKinematicsTorqueAngular accelerationNonlinear systemRobotTransfer functionJoint (building)Dynamics (music)Computer scienceEngineeringPhysicsClassical mechanicsStructural engineeringControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

High gain acceleration feedback for robots with revolute, flexible joints is investigated. The robot is an open kinematic chain with revolute joints. Joints are modeled as linear torsional springs and the joint damping is small: drives are attached at the joints. For fixed theta and with the nonlinear terms considered as disturbances, the transfer function from drive torque to motor angle has only finite zeros, while the transfer function from drive torque to link angle has some infinite zeros. If the joint damping is zero, only infinite zeros appear in this transfer junction. High gains in the acceleration feedback loop from the link angles can be destabilizing due to the presence of these infinite zeros. Stabilizing control laws for the fast dynamics are obtained when using acceleration feedback. Two solutions are proposed. Assuming joint torque can be measured, a joint torque control law can stabilize the fast dynamics: or a compensator can be designed to directly stabilize the fast dynamics in the acceleration feedback loop.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 score0.984
Threshold uncertainty score0.301

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 head0.036
GPT teacher head0.205
Teacher spread0.169 · 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

Citations9
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicDynamics and Control of Mechanical SystemsFrench-language works237,207