Adaptive/Robust Control for Time-Delay Teleoperation
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Bibliographic record
Abstract
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The control of time-delay bilateral teleoperation systems involves a delicate tradeoff between the conflicting requirements of transparency and robust stability. The control design is complicated by latency in data communication between the master and slave sites, as well as uncertainties in the dynamics of operator, master, slave, and environment. This paper proposes a systematic design procedure for improving teleoperation fidelity while maintaining its stability in the presence of dynamic uncertainty and a constant time delay. In a two-step control approach, first local Lyapunov-based adaptive/nonlinear controllers are applied to linearize the system dynamics and eliminate dependency on the master and slave parameters. Teleoperation coordination, subject to parametric uncertainty in the user and environment dynamics, is then achieved by formulating an I/O time-delay <formula formulatype="inline"> <tex Notation="TeX">$H_{\infty }$</tex></formula> robust control synthesis that is solved via its decomposition to the so-called <emphasis emphasistype="italic">adobe</emphasis> problems. The transparency and robust stability properties of the proposed method is examined via numerical analysis. Furthermore, the results are successfully validated in experiments. </para>
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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 | 0.000 | 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 it