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Record W2073697818 · doi:10.1109/isie.2006.295621

From Unconstrained Motion Control to Constrained Case for Holonomic Mechanical Systems

2006· article· en· W2073697818 on OpenAlexaff
K. Melhem, Maarouf Saad, Séraphin C. Abou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHolonomicHolonomic constraintsNonlinear systemConstructiveControl theory (sociology)Mechanical systemConstraint (computer-aided design)Stability (learning theory)Cartesian coordinate systemSimple (philosophy)Computer scienceRobotMotion controlMathematicsControl (management)Artificial intelligenceClassical mechanics

Abstract

fetched live from OpenAlex

This paper discusses a constructive stabilization approach for holonomic mechanical systems. Our approach uses the fact that the nonreduced order dynamics of the constrained system is composed of the original dynamics and the (nonlinear) term of constraint. We show that the stabilization problem of the constrained system given by its obtained nonlinear reduced order dynamics is equivalent to the stabilization problem of the original dynamics under some regularity assumptions. More importantly, using this stabilization technique, very simple stabilizing global output feedback tracking control laws for nonlinear constrained systems with linear original dynamics (e.g., Cartesian structure robots) can be designed. Further, we explain how this output stability result can be discussed for more general mechanical systems. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.458

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 head0.014
GPT teacher head0.220
Teacher spread0.205 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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