Eliminating Chattering in Prosthetic Fingers Using Classic Synergetic Control
Bibliographic record
Abstract
Prosthetic fingers are advancing to help individuals with amputations because of congenital deformities, infections, or accidents have a significant impact on their ability to perform daily tasks as well as their self-confidence.with improved gripping capabilities and natural movement, but controlling them and mitigating chattering remain challenging.To address this, a classic synergetic controller (CSC) was developed using mathematical formulas to control the joint angle position of the Prosthetic finger and accomplish accurate tracking.demonstrating superior performance over Classical Sliding Mode (CSMC) control by 20% in efficiency and robustness.The CSC enabled the prosthetic finger to reach and maintain the desired position angle in 9 seconds without chatter and successfully eliminated chattering under uncertainty, a previously unaddressed issue in prosthetic finger control.The CSC system provided global stability and flexibility in responding to parameter changes, allowing for precise tracking of the finger's movement.These encouraging findings point to a major impact on upcoming developments in the production of prosthetic fingers, opening up new possibilities for use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".