End-effector trajectory inversion of a single flexible link manipulator with non-zero initial states
Bibliographic record
Abstract
The nonminimum phase characteristics of a single flexible link manipulators (SFLM) is a barrier in the application of existing causal end-effector trajectory inversion methods. The available end-effector trajectory inversion results in a pre-actuation base torque and does not tolerate the existence of the non-zero initial states. In this article a new method for the end-effector trajectory inversion of SFLM with non-zero initial states is introduced which does not lead to pre-actuation. This method can be applied when the desired end-effector trajectory needs to be changed or corrected during the maneuver or when a SFLM is initially bent due to its interaction with the surroundings. The result of a simulation study for an initially bent SFLM is also included. While the method is introduced for the end-effector trajectory inversion of SFLM with non-zero initial states, it can be used for the inversion of any linear nonminimum phase single-input single-output system with non-zero initial states.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".