DISTURBANCE OBSERVER-BASED TRAJECTORY FOLLOWING CONTROL OF NONLINEAR ROBOTIC MANIPULATORS
Bibliographic record
Abstract
Robotic manipulators are highly nonlinear and coupled dynamic systems, which may be subject to different types of unknown disturbances such as joint frictions and end-effector external payloads. Such disturbances, when unaccounted for, cause poor tracking performance of the robot and may even destabilize the robot control system. In this paper we propose a novel nonlinear control scheme for robotic manipualtors subject to disturbances using the concept of disturbance observer-based control by modifying the disturbance observers proposed in [1] and [2]. The proposed control scheme and disturbance observer guarantee global asymptotic position and disturbance tracking and remove the previous restrictions on the number of degrees of freedom (DOFs), joint types, or manipulator configuration. Computer simulations are presented for a 4-DOF SCARA manipulator to show the effectiveness of the proposed disturbance observer-based control scheme.
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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) | 0.000 | 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 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".