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Record W4226092060 · doi:10.2514/1.g005169

Pose Tracking Control for Spacecraft Proximity Operations Using the Udwadia–Kalaba Framework

2022· article· en· W4226092060 on OpenAlexaff
Abin Alex Pothen, Alexander Crain, Steve Ulrich

Bibliographic record

VenueJournal of Guidance Control and Dynamics · 2022
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)Nonholonomic systemSpacecraftLyapunov functionController (irrigation)Position (finance)Lyapunov stabilityHolonomicComputer scienceHolonomic constraintsEngineeringControl (management)Mobile robotRobotPhysicsArtificial intelligenceNonlinear systemAerospace engineering

Abstract

fetched live from OpenAlex

This paper develops an analytical dynamics-based approach for simultaneous position and orientation tracking control of a chaser spacecraft with respect to an uncontrolled target. The control requirements are formulated as holonomic or nonholonomic constraints, which are expressed as linear and angular acceleration constraints. The complete six-degree-of-freedom formulation of the Udwadia–Kalaba-based pose tracking controller generating exact real-time control forces and torques is presented. For design purposes, the method assumes a precise knowledge of the system parameters and states, along with perfect control action by the actuators. The exponential convergence of the constraint dynamics is proven using the Lyapunov stability theory. Simulation results demonstrate exponentially stable position and orientation tracking for close-proximity operations in perturbed low Earth orbits. Finally, the controller is experimentally validated using the Spacecraft Proximity Operations Testbed at Carleton University.

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)0.001
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 score0.883
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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