Actuator Placement Optimization and Adaptive Vibration Control of Plate Smart Structures
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Bibliographic record
Abstract
In this paper, a performance criterion is proposed for the optimization of piezoelectric patch actuator locations on flexible plate structures based on maximizing the controllability grammian. This is followed by the determination of parameters required for actuator location optimization through Structuring Analysis in ANSYS Finite Element Analysis Package. Genetic Algorithm is then used to implement the optimization. Finally, with the actuators bonded on optimized locations, a filtered-x LMS-based multichannel adaptive control is applied to suppress vibration response of the plate. Numerical simulations are performed in suppressing tri-sinusoidal response at three points of the plates. The results show that the developed actuator placement optimization methodology is very effective in searching for the optimal actuator locations that minimize the energy requirement of vibration control. The control algorithm is also demonstrated to be efficient and robust in the smart structure vibration control.
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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 | 0.000 |
| 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 it