Adaptive passivity-based control of a flexible-joint robot manipulator subject to collision
Bibliographic record
Abstract
In this paper, passivity-based methods are used to perform tracking control of flexible robot manipulators subject to impact collision. The model taken for colliding system is an n-degree of freedom body moving in the manipulator’s workspace. Impulsive forces generated in the course of impact cause sudden changes in velocity/acceleration of the links of robot and the colliding system. On the other hand, under-actuated systems subject to impact are likely to have instabilities, or poor transient responses, due to excitation of some un-actuated states. The proposed adaptive passivity-based controller not only improves the post-impact transient response of the under-actuated system (e.g. flexible-joint robot), but also needs no force sensor to measure impulse force during the impact phase of robot motion. The main advantage of the proposed controller relative to model-based inverse-dynamic algorithms is its highly robust characteristics in dampening effects of oscillation right after impact collision for an under-actuated system. This can be done through the introduction of an energy-storage function which incorporates the effects of both actuated and un-actuated states of the system.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".