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Record W1976633314 · doi:10.1243/09544100jaero405

Satellite formation flying using variable structure model reference adaptive control

2009· article· en· W1976633314 on OpenAlexaff
K. Shahid, Krishna Dev Kumar

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsControl theory (sociology)Control reconfigurationLyapunov functionAdaptive controlRobustness (evolution)Computer scienceVariable structure controlState variableSliding mode controlNonlinear systemControl (management)Physics

Abstract

fetched live from OpenAlex

In this paper a variable structure model reference adaptive control technique for spacecraft formation flying is proposed. The system consisting of a leader and a follower satellite is considered. The stability of the proposed controller is established using a Lyapunov function. Also, the robustness of the control law to non-linearities and external disturbances is presented. A reference model suitable for formation reconfiguration is then established. The performance of the proposed controller is tested through numerical simulation of the governing non-linear equations of motion and is applied for both formation keeping and formation reconfiguration. The effect of the control parameters on tracking performance and fuel consumption is examined. The effects of initial state errors, leader satellite eccentricity, constant perturbation, and differential J 2 are also considered. The numerical results demonstrate the effectiveness of the proposed control technique for satellite formation flying. In the case of the formation reconfiguration, the proposed controller outperforms the adaptive sliding mode control.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2009
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace EngineeringSame topicSpacecraft Dynamics and ControlFrench-language works237,207