Composite Nonlinear Generalized Predictive Control for Spacecraft Formation Flying Under Disturbances
Bibliographic record
Abstract
The Spacecraft Formation Flying mission's relative motion trajectory tracking is a nonlinear optimal control problem. A class of receding-horizon control for nonlinear systems based on Nonlinear Generalized Predictive Controller design provides a closed-form solution for an optimal control problem. The application of standalone Nonlinear Generalized Predictive Controller for relative motion tracking control problem has observed non-zero steady state errors due to inherent system nonlinearities. In this context, this paper demonstrates the composite optimal controller structure with Nonlinear Generalized Predictive Controller and nonlinear disturbance observer design to obtain a precise tracking. Additionally, the composite optimal controller is derived to form the Proportional, Derivative and Integral controller structure for the relative motion control problem to obtain an analytical, onboard-compatible and computationally efficient optimal controller. The resulting controller is shown to be suitable to be used for perturbed near-circular orbits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".