Tuned Modal Control of a Space-Based Deployable Manipulator
Bibliographic record
Abstract
This paper develops an intelligent hierarchical controller for vibration control of a deployable manipulator. The emphasis is on the tuning of a low-level direct controller using an upper level knowledge-based tuner so as to improve the performance of the manipulator. In the present development, a conventional modal controller is used as the direct controller. First a fuzzy inference system (FIS) is developed for controller tuning. The FIS and the modal controller are integrated into a hierarchical control system for use with the deployable manipulator. An example is presented to illustrate the application of the hierarchical control system for suppressing vibrations caused by initial disturbance of a space-based deployable manipulator system. The simulation results show that the developed system is very effective in suppressing vibrations induced due to an initial disturbance at the tip of a manipulator module. Performance of the modal controller is significantly improved through knowledge-based tuning.
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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".