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Record W2328810747 · doi:10.1115/detc2011-47967

On the Accuracy of Assumed Mode Modeling for Flexible Manipulators

2011· article· en· W2328810747 on OpenAlexaff
Fatemeh Heidari, M. Vakil, Reza Fotouhi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsControl theory (sociology)Transfer functionDisplacement (psychology)Mode (computer interface)Pole–zero plotFunction (biology)MathematicsComputer scienceEngineeringControl (management)

Abstract

fetched live from OpenAlex

Assumed mode shape method (AMM) has been widely used to derive finite degree-of-freedom (DOF) dynamic model for flexible link manipulators, which theoretically have infinite DOF dynamics. For single flexible manipulator, this approximation changes locations of the zeros of transfer function, between base torque and end-effector displacement. The change in locations of zeros considerably affects accuracy of the model and hence the performance of model-based controllers. This paper presents a comprehensive study on the change in location of zeros due to the truncation associated with AMM. It is shown that the locations of zeros of AMM model depend on four non-dimensional parameters while the locations of the analytical model depend on only two non-dimensional parameters; AMM zeros are obtained from AMM model while analytical zeros derived from infinite order model. A thorough study on the differences between AMM zeros and analytical zeros versus number of mode shapes as well as all the physical parameters is performed. Moreover, guidelines are provided to select the numbers of mode shapes such that the AMM zeros become close to the analytical zeros. These guidelines can easily be used by control engineers and thus makes them valuable for modeling and control of flexible robot manipulators.

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 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 score0.814
Threshold uncertainty score0.184

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 head0.050
GPT teacher head0.237
Teacher spread0.187 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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