Moving Mass and Reaction Compound Control System Design for Reentry Aircrafts
Bibliographic record
Abstract
Moving mass control (MMC) method is of benefit to reentry aircrafts in shape maintenance, energy consume reduction and load capability increase. However, as an aerodynamic manipulating method, MMC partially lacks ability to perform effectively during a whole airspace flight. To achieve reentry aircrafts control system design goal of high performance and low energy cost, we propose a moving mass and reaction compound control system design method in this paper. Firstly, dynamic models are established for a reentry aircraft actuated by moving mass and reaction compound control system, including MMC actuator models. Secondly, moving mass control periodic equivalent torque (MMCPET) is defined, and an optimal torque distribution compound control method based on MMCPET prediction is presented. The optimal object of torque distribution is minimizing difference from MMCPET and control torque command given by virtual controller. Finally, comparison simulations are performed to demonstrate validity of the proposed method. Simulation results show that the proposed compound control is more effective than moving mass control. Also, even if performance of compound control is nearly the same as that of reaction control, thrust impulse requirement of the former is close to 1/5 of the latter.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".