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Record W4390777632 · doi:10.1109/tac.2024.3351552

Flexible Single-Link Manipulators Control Based on a Full-Order Transfer Function Model

2024· article· en· W4390777632 on OpenAlexafffund
Reza Mohsenipour, Guangjun Liu

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2024
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Transfer functionLink (geometry)Payload (computing)Reduction (mathematics)Controller (irrigation)Function (biology)Stability (learning theory)Computer scienceControl engineeringMathematicsControl (management)Engineering

Abstract

fetched live from OpenAlex

This article presents a solution for the problem of flexible single-link robotic manipulators control in the frequency domain based on a full-order transfer function model. A transfer function model is derived from the partial differential equations of the flexible single-link manipulator system without any model order reduction. Conditions are obtained for the stability of the derived model that takes into account the payload mass changes. Employing these conditions, desired regions are obtained for the parameters of an output feedback controller which guarantee the stability and prescribed phase and gain margins as the design criteria. The regions consist of three types of boundaries of which two types provide necessity and sufficiency for the design criteria and the other provides sufficiency. A numerical example is given to demonstrate the suggested approach, showing it is less conservative than the other existing methods using reduced-order models.

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 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 score0.994
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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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 teacher head, not a consensus.

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

Citations9
Published2024
Admission routes2
Has abstractyes

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