SLIDING-MODE CONTROL FOR TELE-ROBOTIC NEUROSURGICAL SYSTEM
Bibliographic record
Abstract
This paper presents a sliding-mode control (SMC) design for the tele-robotic neurosurgical system. The proposed tele-robotic neurosurgical system with force, video, and voice feedback is introduced first, which can be tele-operated over the Internet. However, delay on the Internet may cause the proposed system unstable. It is a critical issue to deal with time delay in the proposed system. Based on an uncertain delayed stochastic model of the proposed system, the SMC is employed. In this paper, both constant and varying time delay are considered. The sliding surface was designed to maximize the calculable set of admissible delays. By defining Lyapunov--Krasovskii functions, the conditions for the existence of the sliding regime were studied. In addition, linear matrix inequalities were employed for the optimization procedure. Finally, results of simulation proved feasibility and efficiency of the proposed method.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".