Finite‐time attitude‐tracking control for rigid spacecraft with actuator failures and saturation constraints
Bibliographic record
Abstract
Summary In this article, the problem of finite‐time attitude‐tracking control for rigid spacecraft is addressed. Uncertainties caused by external disturbances, unknown inertial matrix, actuator failures, and saturation constraints are tackled simultaneously. First, a smooth function that is more qualified to approximate the standard saturation characteristics is presented to deal with the actuator saturation constraints. Second, a fast nonsingular terminal sliding mode (FNTSM) manifold is constructed as a foundation of controllers design. By incorporating the fuzzy logic system into FNTSM technique, a less demanding solution of coping with model uncertainties is provided because the requirement of a prior knowledge of unknown inertial parameters and external disturbances in many existing achievements is removed. To reduce the number of parameters to be estimated, the norm approximation approach is exploited. Subsequently, an antichattering attitude controller is presented such that all the tracking errors converge into arbitrary small domains around the origin in finite time. The result is further extended to obtain a fault‐tolerant controller against completely failed actuators. Finally, numerical simulation is conducted to verify the effectiveness of the proposed control scheme and comparison with relevant literature demonstrates its high performance. Furthermore, an experiment for the large satellite Hubble Space Telescope is carried out to validate the practical feasibility.
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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 | 0.001 |
| 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 | 0.000 |
| 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".