Extended fuzzy logic controller for uncertain teleoperation system
Why this work is in the frame
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Bibliographic record
Abstract
Teleoperation systems allow a surgeon to perform a remote distance operation with or without magnification. Nonlinearity and unknown dynamics of master and slave robots, in teleoperation systems, make it challenging to guarantee stability and convergence of the position tracking error in such systems. This paper presents an interval Type-2 Fuzzy (T2F) logic controller to control position of a teleoperation system without knowing dynamics of master and slave robots. Interval T2F controller have been recently applied in many engineering fields while understanding the control potentials of interval T2F still have been an open question for researches. The control methodology is baseline optimized Type-1 Fuzzy (T1F) Controllers. Although, the performance of T1F controller, deals with unknown dynamics, is reasonable, but in comparison to interval T2F controller, when uncertainties are increased, it has weaker performance. The performance of the controller has been evaluated on the test — bed consists of two Novint Falcon robots as the master and slave. The experimental results show improved performance of interval T2F controllers in comparison to T1F controllers.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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