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Record W2749855088 · doi:10.1080/00207721.2017.1360963

Robust adaptive vibration control for an uncertain flexible Timoshenko robotic manipulator with input and output constraints

2017· article· en· W2749855088 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Systems Science · 2017
Typearticle
Languageen
FieldEngineering
TopicStability and Controllability of Differential Equations
Canadian institutionsnot available
FundersBasic Research Program of Jiangsu ProvinceUniversity of Science and Technology BeijingNatural Science Foundation of Beijing MunicipalityUniversity of British ColumbiaNational Natural Science Foundation of ChinaRoyal Society
KeywordsControl theory (sociology)Robot manipulatorBoundary (topology)Convergence (economics)VibrationBounded functionManipulator (device)Vibration controlRobust controlControl engineeringComputer scienceControl (management)MathematicsRobotic armEngineeringControl systemArtificial intelligence

Abstract

fetched live from OpenAlex

The problems of the constraints and the vibration suppression are investigated for the flexible Timoshenko robotic manipulator in this paper. Robust adaptive boundary control laws with the disturbance observes are designed to guarantee the convergence of the feedback flexible Timoshenko robotic manipulator system with the uncertain parameters and the states are proven to be uniform bounded. In addition, the proposed boundary controls are verified to be effectiveness by the numeral experiments.

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)0.001
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 score0.754
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.066
GPT teacher head0.280
Teacher spread0.214 · 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