Integrated asymmetric stop operator based model for strain stress hysteresis characteristics of cable driven robots loaded longitudinally
Bibliographic record
Abstract
Beside the output-input hysteresis, the longitudinally loaded cables of medical robotics such as RAVEN II exhibit asymmetric saturated strain-load hysteresis loops. This study investigates modeling the hysteresis nonlinearities of these cables using a stop-operator based Prandtl-Ishlinskii (SPI) model that is integrated with a memoryless function. The stop-operator based model is employed to account for the hysteresis nonlinearities, while the memoryless function is introduced to characterize saturation and asymmetric effects. A numerical example is presented to compare the properties of the proposed model with the classic SPI model. The response of the suggested model was evaluated on the hysteresis properties of two different cables subjected to triangular harmonic input of 0 to 0.001 with 6.25 × 10-5strain/s. The characterization error of the thick cable was found as 1.55 %, while the error was calculated as 1.25 % for the thin cable. The relative significance of the proposed model was further examined by comparing the measured data with the classic SPI model. The results showed that the classic model yields substantial characterization errors when the asymmetry and saturation effects of the strain-load hysteresis loops are ignored.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".