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Record W1519985716 · doi:10.1109/87.944464

Motion control systems with ℋ/sup ∞/ positive joint torque feedback

2001· article· en· W1519985716 on OpenAlexaff
Farhad Aghili, M. Buehler, John M. Hollerbach

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsMcGill UniversityCanadian Space Agency
Fundersnot available
KeywordsControl theory (sociology)TorqueDecoupling (probability)ActuatorEngineeringStall torqueSensitivity (control systems)Damping torqueMotion controlControl engineeringComputer scienceDirect torque controlInduction motorPhysicsControl (management)Robot

Abstract

fetched live from OpenAlex

In this work, a new /spl Hscr//sup /spl infin// joint torque feedback approach is proposed which takes into account the actuator's finite bandwidth dynamics, and minimizes the system's sensitivity to load torque disturbances and load dynamics. We also address implementation issues such as the development of a hydraulic dynamometer testbed for measurement of the disturbance sensitivity and of an innovative method for identifying the actuator dynamics. Experiment results with our experimental direct-drive motor demonstrate that the additional /spl Hscr//sup /spl infin// positive torque feedback greatly improves the disturbance attenuation and load decoupling properties of a simple PID motion controller. The optimal torque feedback also reduces the tracking error when dealing with a dynamic load while, unlike the conventional unity joint torque feedback, maintaining robust stability.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.183
Teacher spread0.177 · 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

Citations29
Published2001
Admission routes1
Has abstractyes

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