Passive wave variable control of haptic interaction with an unknown virtual environment
Bibliographic record
Abstract
The wave variable transformation cannot be exploited for the control of sampled-data and discrete-time systems without precaution. This paper shows that connecting a haptic interface to a discrete time virtual environment through a wave variable controller can inject energy into the haptic feedback loop and thus jeopardize the stability of the haptic interaction. The connection involves a one step computational delay when the virtual environment is not known prior to starting the interaction. Using the Jury-Marden stability criterion, the paper investigates the effect of this computational delay on the stability of wave variable control of haptic interaction with a virtual wall. It also develops a time domain passivity analysis to compute the energy injected in the wave variable transformation by the computational delay. Then, it proposes an algorithm for dissipating the extra energy and restoring the passivity of the wave variable transformation. The paper concludes with the experimental validation of the energy dissipating algorithm.
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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) | 0.001 | 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 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".