Backstepping control based on neural network estimation
Why this work is in the frame
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Bibliographic record
Abstract
This paper is implementing a backstepping controller to a quadrotor that is subject to unknown disturbances and uncertainty in dynamics. Estimation and approximation of unkowns and uncertainties are performed by using Radial Base Function Neural Network (RBFNN). Along with a backstepping controller, they provide robustness to the robotic systemdespite of the presence od uncertainties. The RBFNN's output layer is utilized as an estimator then compensation eliminates the undesired effect occurs due to uncertainties. As a result, faster error convergence is achievable. A Lyapunov function was used to analyze the closed loop system, and Matlab/Simulink was used to evaluate the system performance. The demonstrated results prove the efficiency of the proposed approach.
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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) | 0.000 | 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) | 0.000 | 0.001 |
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