Adaptive Robust Control of Networked Multi-Manipulators with Time-Varying Delays
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Bibliographic record
Abstract
In this paper, an adaptive non-singular terminal sliding mode (NTSM) method is proposed for a networked multi-manipulator system. This paper aims at dealing with multiple challenging control problems. Firstly, a robust and adaptive controller is proposed to deal with random time-varying network delays in the existence of the parametric uncertainties in system dynamics, unknown frictions, and external disturbances. Secondly, the bounds of the uncertainties, frictions, and disturbances are not required as a prior by the robust adaptive control algorithm, while three compensatory bounds are calculated in real-time to compensate the errors introduced by the network delays and the acceleration estimation. Thirdly, for the network with the weak connectedness and unknown time-varying delays, the followers are able to synchronize to a time-varying leader trajectory. Numerical simulation results of a team of two degree-of-freedom (DOF) manipulators show that the designed control system ensures the good synchronizing performance with small and bounded tracking errors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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