Observer-Based Adaptive Output Feedback Control for Miniature Aerial Vehicle
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Bibliographic record
Abstract
In this paper, we propose an observer-based adaptive output feedback flight tracking system for the miniature aerial vehicle (MAV) in the presence of bounded uncertainty. The proposed design has two parts. First, a state feedback based nonlinear adaptive control algorithm is designed by assuming that all the states are available for feedback. The convergence analysis with the state feedback based design is derived by using the Lyapunov method. Second, we replace the unknown velocity states by a linear observer to develop adaptive output feedback flight tracking system for the MAV. The convergence analysis with the observer-based output feedback design is shown by using a singularly perturbed method. The analysis shows that the performance achieved under state feedback can be recovered by using an output feedback based design. Evaluation results are given to demonstrate the effectiveness of the proposed design for real-time applications.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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