DOB-Based Neural Control of Flexible Hypersonic Flight Vehicle Considering Wind Effects
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Bibliographic record
Abstract
This paper investigates the disturbance observer (DOB)-based neural adaptive control on the longitudinal dynamics of a flexible hypersonic flight vehicle (HFV) in the presence of wind effects. The coupling effect between flexible states and rigid body, and the accessional angle of attack (AOA) due to wind, is modeled as unknown disturbance, where the nonlinear DOB is constructed using the neural approximation. For the weight update in neural networks (NNs), a novel algorithm is proposed with the additional prediction error derived from the serial-parallel estimation model (SPEM) using both neural approximation and disturbance estimation. Different from previous work, the wind effect is taken into the hypersonic flight dynamics for realistic analysis, and the novel controller is designed using compound estimation, where the NN and the DOB are constructed to deal with aerodynamic uncertainty and unknown disturbance. Simulation studies of a flexible HFV with wind effects show that the proposed controller can achieve high tracking accuracy, while the compound estimation can closely follow the system uncertainty with fast convergence.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it