Novel adaptive iterative observer based on integral backstepping control of a wearable robotic exoskeleton
Why this work is in the frame
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Bibliographic record
Abstract
Assisted control seeks to help subjects to perform physical movements of the body, which they cannot do by themselves. Passive rehabilitation therapy is very important and vital after the stroke accident. In this functioning mode, the subject is completely passive during the movement. The robot brings the injured upper arm of the patient to perform repetitive therapeutic exercises. In this case, the subject's force and the uncertainties caused by repetitive motion, such as mechanical and actuator fatigue, are considered as external disturbances that negatively influence the performance of the exoskeleton robot. To ensure the stability, robustness, and accuracy of the robot, a robust iterative observer based on nonlinear integral backstepping control was implemented with designed exercises performed by subjects. Experimental results show the effectiveness of the proposed control to deal with the external force and repetitive/periodic uncertainties.
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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 | 0.001 | 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