Causal inversion of a single-link flexible-link manipulator via output planning
Bibliographic record
Abstract
Recently, a method was introduced by Bensoman and Le Vey (July 2003) for the stable inversion of a single-input single-output (SISO) non-minimum phase system through the employment of output planning. The use of a causal input via output planning permits the initial conditions to be freely selected. In the application of this method to a single-link flexible-link manipulator (SFLM), for any initial conditions a polynomial is sought for the end-effector's trajectory that cancels the effects of the internal instability of the inverse system. A drawback of this method, however, is that allows for the development of only one polynomial for any initial conditions imposed on the input and output. An extension of this method is proposed in this paper which does not suffer from this drawback. This extension employs exponential functions to define the end-effector's trajectory, which leads not to just one solution, but to a family of solutions. The results of some simulation studies that verify the proposed extension are included.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".