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Record W7133018893

Comparison of Numerical Methods for Low-Thrust Spacecraft Trajectory Optimization

2024· dissertation· W7133018893 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

VenueTSpace · 2024
Typedissertation
Language
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTrajectoryTrajectory optimizationControl theory (sociology)SpacecraftOrbital maneuverOrbit (dynamics)RendezvousThrustOptimal control
DOInot available

Abstract

fetched live from OpenAlex

Low-thrust spacecraft propulsion systems enable fuel-efficient trajectories through space but the resulting trajectory optimization problems can be challenging. In this work, various numerical approaches for designing such low-thrust trajectories have been analyzed and compared. First, the Hermite-Legendre-Gauss-Lobatto (HLGL) and the Legendre-Gauss pseudospectral (PS) direct collocation methods, which are used for transcribing an optimal control problem into a nonlinear programming problem, have been compared for a minimum-time low-thrust Earth-to-Mars transfer problem. Next, a novel control law, the RQ-Law, is presented for generating low-thrust three-dimensional multi-revolution coasting-enabled rendezvous trajectories with a moving target, based on modified equinoctial elements. It builds upon the Q-Law, which is a Lyapunov feedback control law for orbital transfers. The RQ-Law offers an alternate method of determining the Lyapunov-optimal thrust angles used for both orbital transfer and phasing. It also provides a new target semimajor axis augmentation scheme that is demonstrated to perform phasing in a wide range of eccentric orbits. Compared with existing low-thrust Lyapunov rendezvous methods, the RQ-Law can include coasting arcs in the trajectory to save fuel as well as account for a minimum periapsis radius constraint. Alongside a thorough qualitative comparison of the RQ-Law, the performance of this law is evaluated numerically by using it to generate a rendezvous trajectory involving large changes in all six orbital elements. This performance was compared with a hybrid control law composed of an existing modified equinoctial Q-Law and a spiral phasing law. Three trade studies were performed that studied, respectively, the effects of the chaser departure point, the point at which low-thrust phasing is initiated, and the target orbit eccentricity, on the RQ-Law performance. Finally, to investigate the use of the RQ-Law to help mitigate the problem of space debris, we develop a low-thrust multiple-rendezvous trajectory to traverse a predetermined sequence of targets. The RQ-Law advances the state-of-the-art of the Q-Law and provides an integrated design tool for preliminary low-thrust rendezvous trajectory generation without needing an initial guess. The contributions of this thesis can be used for a variety of planetocentric and interplanetary space missions that use low-thrust electric propulsion.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.660
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.020
GPT teacher head0.411
Teacher spread0.391 · 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