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Record W1842994408 · doi:10.1109/acc.1995.529273

Adaptive motion/force control of mechanical systems with nonholonomic Pfaffian constraints

2005· article· en· W1842994408 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNonholonomic systemPfaffianControl theory (sociology)Mechanical systemConstraint (computer-aided design)Controller (irrigation)Adaptive controlProperty (philosophy)Computer scienceMathematicsRobotControl (management)Artificial intelligenceMobile robot

Abstract

fetched live from OpenAlex

The contribution of this work relates to two subjects. In the first part of the paper the authors present a novel dynamic description of mechanical (Lagrangian) systems with nonholonomic (Pfaffian) constraints. This development was motivated by the need for a convenient and simple dynamic model for the controller. Essentially, the new element of this development is QR decomposition of the constraint matrix. Following this decomposition, the authors have proven a new dynamic property of the considered system. This property allows the authors to express the system dynamics in terms of a new reduced-order state vector. The second part of the work is concerned with development of the adaptive position/force controllers for general Lagrangian systems with Pfaffian constraints. Two cases are elaborated: (i) motion/force tracking control with known system parameters, and (ii) adaptive control in the presence of uncertainties. The adaptive control law guarantees the uniform ultimate boundness of the tracking error.

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)0.000
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 score0.957
Threshold uncertainty score0.460

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 head0.004
GPT teacher head0.169
Teacher spread0.164 · 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

Quick stats

Citations7
Published2005
Admission routes1
Has abstractyes

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