Motion Control of Dielectric Viscoelastomer Actuator With Variable Load Based on Cerebellar Model Articulation Neural Network
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Bibliographic record
Abstract
Dielectric viscoelastomer actuators (DVAs) possess humanlike muscle softness and large stretch, which have demonstrated great application potential in the field of soft biomimetic robots. At present, the high-precision motion control of the DVA is still challenging due to its complicated dynamic characteristics, especially when its load varies. To provide a feasible solution to this issue, this article presents a hybrid control architecture, which includes a cerebellar model articulation neural network (CMANN) and a proportional integral differential controller (PIDC). The CMANN is used as an inverse compensator to mitigate the complicated dynamic characteristics of the DVA and the PIDC is employed to enhance the control system's robustness. The proposed control architecture is validated experimentally via a DVA-based motion control platform. The experimental results demonstrate that the DVA can precisely track various reference trajectories even though its load varies during the control process, expanding applications of the DVA in emerging fields.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it