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Self Recovery Phenomenon of Mechanical Systems With Unactuated Cyclic Variables due to Damping-Like Forces

2012· article· en· W2037410584 on OpenAlexaff
Dong Eui Chang, Soo Jeon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhenomenonControl theory (sociology)Classical mechanicsMaterials scienceMechanicsPhysicsComputer science

Abstract

fetched live from OpenAlex

The conservation of momentum can be useful in designing control laws for underactuated mechanical systems. However, the momentum is conserved only for unactuated variables with symmetry. If a symmetry-breaking force is applied to a system, the momentum is not conserved any longer in general. The main objective of this paper is to show that there exist forces linear in velocity such as the damping force that break the symmetry but induce a new conserved quantity in place of the original momentum map. This paper formalizes that such a new conserved quantity can be constructed by combining the time integral of a general damping force and the original momentum map associated with the symmetry. Especially, we show that the new conserved quantity can exist for multiple variables with symmetry. From the perspective of stability theories, the major implication of the new conserved quantity is that the corresponding variables possess the self recovery phenomenon, i.e. they will be globally attractive to the initial condition of the variables. What is fundamental in the damping-induced self recovery is not the positivity of the damping coefficient but certain properties of the time integral of the damping force. Self recovery effect and theoretical findings are demonstrated by simulation results using a two-link manipulator and a planar pendulum. The results in this paper will be useful in designing and controlling mechanical systems with underactuation.Copyright © 2012 by ASME

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 score0.694
Threshold uncertainty score0.667

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 head0.006
GPT teacher head0.181
Teacher spread0.175 · 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
Published2012
Admission routes1
Has abstractyes

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