A servocompensator approach to the control of flexible space robotic manipulators with application to teleoperation
Bibliographic record
Abstract
A control concept applicable to the teleoperation of multilink, structurally flexible manipulators, based on commanded velocity of the end-effector, is presented. A velocity-tracking controller is used to effect the desired motion of the manipulator. The controller seeks to minimize the velocity tracking error at the cost of allowing the links to flex. This controller is designed by precomputing gains based on a set of dynamics equations, obtained by linearizing over a space of predetermined geometrical configurations and casting them into state-space form. Appropriate real-time controller gains are determined by interpolating between a subset of those precomputed gains, corresponding to geometrical configurations, in the neighborhood of the desired configuration. The system is augmented with a second-order integrator (for torque smoothing) and further augmented by a servocompensator whose input is the error between the actual end-effector velocity and the reference (command) velocity. Although principally motivated by teleoperation, the controller can also be used in an autonomous mode, which is the focus of this paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".