Direct Neural-Adaptive Control of Robotic Manipulators using a Forward Dynamics Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper uses a forward-dynamics approach to achieve direct neural-adaptive control of a two-link robotic manipulator. Cerebellar model articulation controllers model the forward dynamics. Previous approaches in the literature use an inverse-dynamics approach because online estimation of the inertia matrix is difficult. The proposed method succeeds by using a supervisory inertia matrix when updating the neural network weights. The supervisory matrix does not need to accurately model the real inertia matrix to achieve accurate trajectory tracking. This remains true even when significant unmodelled payloads are added or, equivalently, when there is large uncertainty in the inertia matrix. A Lyapunov analysis establishes the ultimate uniform boundedness of all signals
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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 | 0.000 |
| 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