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Record W2061725852 · doi:10.1243/09544100jaero269

Satellite attitude control using solar radiation pressure based on non-linear sliding mode control

2008· article· en· W2061725852 on OpenAlexafffund
Tejashkumar R. Patel, Krishna Dev Kumar, Kamran Behdinan

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsToronto Metropolitan University
FundersCanada Research Chairs
KeywordsControl theory (sociology)Sliding mode controlAttitude controlSatelliteRobustness (evolution)Feedback linearizationSolar sailLinearizationComputer scienceControl engineeringNonlinear systemEngineeringControl (management)Aerospace engineeringSpacecraftPhysics

Abstract

fetched live from OpenAlex

The paper proposes the use of solar radiation pressure for satellite attitude control using non-linear sliding mode control (SMC). The system comprises a satellite with two-oppositely placed solar flaps. A non-linear SMC approach has been adopted to develop control law for suitably rotating the solar flaps to achieve desired satellite attitude performance. The detailed numerical simulation of the governing non-linear system equation of motion including the effects of various system parameters on the controller performance, establishes the feasibility of the proposed control strategy. The numerical simulation matches with the analytical results. Furthermore, the proposed controller is found to be robust against external disturbances and its performance is superior in comparison to feedback linearization control. Thus, the robustness of the proposed control strategy makes it attractive for future space applications.

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 score0.001
Threshold uncertainty score0.002

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 head0.008
GPT teacher head0.200
Teacher spread0.193 · 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
Published2008
Admission routes2
Has abstractyes

Explore more

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