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Record W3173447544 · doi:10.2514/6.2012-4620

Direct Fuzzy Adaptive Control of a Manipulator with Elastic Joints

2012· article· en· W3173447544 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

VenueAIAA Guidance, Navigation, and Control Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsManipulator (device)Computer scienceControl theory (sociology)Fuzzy control systemAdaptive controlControl (management)Fuzzy logicControl engineeringRobotArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

The use of harmonic drive gear boxes in space robotic applications offer several attractive properties, such as high reduction ratio, compact size, low mass, and coaxial assembly. However, the flexibility effects of this type of gear mechanism in the joints of robotic manipulators are significant enough to make real-time control challenging. This paper addresses the problem of fuzzy adaptive trajectory control of space manipulators that exhibit elastic vibrations in their joints and that are subject to parametric uncertainties and dynamics modeling errors. The developed control scheme uses a fuzzy adaptation mechanism that varies in real-time the gains of a slow control term designed to stabilize the rigid dynamics, and a linear correction term to further reduce the elastic vibrations at the joints. The proposed controller is validated in numerical simulations in a trajectory tracking scenario by a flexible-joint manipulator. Simulation results suggest that the controller is robust to uncertainties in joint stiffness coefficients and to modeling errors, and yields improved tracking performance compared with conventional flexible-joint control strategies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.752

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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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