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Record W1680450188 · doi:10.1109/cdc.1989.70433

Control of robotic manipulators with flexible joints during constrained motion task execution

2003· article· en· W1680450188 on OpenAlexaff
James K. Mills

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceControl theory (sociology)Flexibility (engineering)ActuatorMotion controlTask (project management)Control engineeringRobotMotion (physics)Control (management)EngineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

The control and stability of manipulators with flexible joints during constrained-motion task execution is investigated. A singular perturbation model that represents the joint flexibility caused by compliance in actuator drive shafts as well as transmission systems is developed. The concept of composite control is used to formulate a control for the slow and fast subsystem dynamics. The slow subsystem control is comprised of a corrective control which uses the concept of an integral manifold to compensate for flexibility effects, in conjunction with a rigid control law, based on the rigid manipulator constrained dynamic equations of motion. With this control applied to the robotic system, it is demonstrated that the high-frequency flexible modes do not destabilize the system. Results of a numerical simulation of a two-joint manipulator during execution of a constrained-motion task are presented to support the analytic results.>

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.172
Teacher spread0.166 · 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
GenreMethods

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

Citations26
Published2003
Admission routes1
Has abstractyes

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