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Record W2099458017 · doi:10.1109/iros.1997.656557

Control of space free-flyers using the modified transpose Jacobian algorithm

2002· article· en· W2099458017 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransposeJacobian matrix and determinantAlgorithmStability (learning theory)Computer scienceControl theory (sociology)MathematicsControl (management)Artificial intelligenceApplied mathematicsEigenvalues and eigenvectors

Abstract

fetched live from OpenAlex

Transpose Jacobian control is one of the simplest algorithms used in manipulator control. However, since it is not dynamics-based, poor performance may occur in applications where high speed tracking is required. In this paper, a modified transpose Jacobian algorithm is presented and applied to control of space free-flyers. This new algorithm employs stored data of the control command in the previous time step, resulting in improved performance. The gains of the modified algorithm do not need to be large, hence the noise rejection characteristics of the algorithm are improved. Stability analysis, based on Lyapunov's theorems, shows that both the standard and the modified transpose Jacobian algorithms are asymptotically stable. Simulations of both terrestrial and space applications show that the tracking performance of this new algorithm is comparable to that of computed torque algorithms, although it does not require a priori knowledge of plant dynamics.

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 score0.981
Threshold uncertainty score0.502

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 head0.023
GPT teacher head0.205
Teacher spread0.181 · 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

Citations25
Published2002
Admission routes2
Has abstractyes

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