On the Stability of a Friction Compensation Strategy for Flexible-Joint Manipulators
Bibliographic record
Abstract
A new control strategy for flexible-joint manipulators with joint friction is proposed. The proposed controller includes two main components: a friction compensating torque, and a composite controller torque to compensate for the friction in the joints and the flexibility of the joints, respectively. The novel approach that is used to compensate for the friction in the joints includes a nonlinear one-state LuGre model and a PD control. The second method of Lyapunov is utilized to find sufficient conditions for the global asymptotic stability of the friction compensating torque and it is shown that the tracking error is bounded as long as appropriate PD gains are chosen. The performance of the proposed controller is experimentally verified using a setup of a two-rigid-link flexible-joint manipulator. Experimental results are presented for different flexibilities of the joints and also for different desired trajectories. These results demonstrate the high performance of the controller under different situations while the tracking error remains very small.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".