Trajectory tracking control of flexible-joint space manipulators
Bibliographic record
Abstract
Operational problems with robots in space relate to several factors. One of the most important factors is the elastic vibrations in the joints. In this paper, control strategies for endpoint tracking of a 12.6 m×12.6 m trajectory by a two-link space robotic manipulator are reviewed. Initially, a manipulator with rigid joints is actuated using a transpose jacobian control law and a model reference adaptive control system that adapts, in real-time, the control gains in response to errors between the actual system outputs and the ideal system outputs defined by a reference model. The rigid-joint dynamics model was pursued further to study a manipulator with flexible joints modeled with linear- and nonlinear-joint stiffness models. Then, the two rigid-joint control schemes were modified using the singular perturbation-based theory and applied for the control of both linear and nonlinear flexible-joint robot models. Finally, the rigid and flexible control systems described in this paper were evaluated in numerical simulations. Simulation results suggested that greatly improved tracking accuracy can be achieved by applying the adaptive control strategies.
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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) | 0.001 | 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".