Velocity observer design for a class of uncertain nonlinear mechanical systems: a self-adaptive fuzzy logic-based approach
Why this work is in the frame
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Bibliographic record
Abstract
This study focused on designing a smooth velocity observer (VO) for mechanical systems whose mathematical model is uncertain. The uncertainties that appear in the observer dynamics are, via utilising their universal approximation property, modelled with fuzzy logics. A novel self-adaptive fuzzy logic (SAFL)-based term in which control representative value matrix (CRVM), centres and widths of membership function are all dynamically updated is used as part of the observer design. Through the application of Lyapunov-type stability analysis techniques, the practical stability of the observed velocity error was guaranteed. The outcomes derived from experimentation on a planar robotic manipulator are showcased to illustrate the performance of the devised VO design.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 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