Direct adaptive neurocontrol of flexible joint robots using localized polynomial networks
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
Presents a novel direct adaptive neurocontrol scheme for flexible joint robots with structural uncertainty and arbitrary nonlinear joint flexibility. The localized polynomial networks are used to represent unknown system dynamics. It is proved that all the signals in the closed-loop direct adaptive neurocontrol systems can be made uniformly bounded and the output tracking errors can be guaranteed to converge globally to a specified neighborhood of zero. Therefore, global stability of the neurocontrol systems is guaranteed. The learning process is fast convergent and needs less computation, due to the usage of the localized polynomial networks. Compared with conventional schemes, this direct adaptive neurocontrol scheme allows robotic dynamics to have more general structure and is more robust to robotic system modeling errors. No link acceleration and jerk measurements are needed, and the control actions are chatter-free.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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