Control of Flexible Payloads Grasped by Actuated Grippers Undergoing Large Rigid-Body Motions: Part II — Controllability and Observability
Bibliographic record
Abstract
Part I of this work models the dynamics of a flexible payload grasped by an actuated gripper undergoing large rigid body motion by a robotic manipulator. In Part II, the controllability and observability conditions of the system are discussed. In Part I, the dynamic model of the actuated flexible payload is derived using the component mode synthesis (CMS) method with addition of actuator constraint, fixed-interface vibration and quasi-static modes. Here, the two-time scale modeling (TSM) technique is employed taking advantage of the two-time scale behavior between the quasi-static modes and vibration modes in the dynamic model. Due to the complexity of the resulting system, the controllability and observability conditions are not trivial. Hence, the controllability and observability study addressed herein becomes essential in showing the advantages of using the CMS and TSM techniques in control system design for the problem. A simulation example demonstrates that simultaneous vibration and quasi-static deformation control is achievable by proper selection of each type of modes.
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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 | 0.000 | 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 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".