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Record W2102260527 · doi:10.1109/tcst.2013.2259593

Stability-Guaranteed Assist-as-Needed Controller for Powered Orthoses

2013· article· en· W2102260527 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)AdmittanceControl engineeringAccelerationEngineeringRoboticsComputer scienceRobotSimulationArtificial intelligenceElectrical impedanceControl (management)

Abstract

fetched live from OpenAlex

This brief describes the assistance regulation controller (ARC), a nonlinear admittance controller for powered orthoses (POs) and wearable robotics that simultaneously facilitates task completion and encourages user effort. This brief also introduces a novel acceleration-limited proportional derivative controller (ALPDC) that guarantees the stability of the ARC's inner position control loop. The stability analysis of the ALPDC shows that this simple and robust position controller promotes safer human-robot interactions in a large class of admittance-controlled haptic devices. Both the ARC and ALPDC are implemented on a one-degree-of-freedom PO designed to assist forearm flexion and extension. Experiments performed by a healthy male subject confirm that the ALPDC guarantees stable user-device interactions and bounded tracking errors during highly dynamic forearm motions that lead to instability with a conventional controller.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.206
Teacher spread0.199 · 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