Design of Vibration Controllers for Flexible Beams Using the Mechatronic Design Quotient (MDQ) Approach
Bibliographic record
Abstract
When using linear dampers for the suppression of vibration in flexible structures, their mounting locations and the damping coefficients have to be chosen properly. In this article, an approach to the optimal design of linear dampers for vibration control in flexible beams based on the mechatronic design quotient (MDQ) is presented. This approach strives to make the optimal concurrent design of the dampers come as close as possible to the performance of an optimal sequential design of uncoupled subsystems. The MDQ approach provides a practical way to evaluate the performance of multi-criteria design. It also provides an insight into the performance degradation of various subsystems caused by dynamic coupling effects in the overall system. In the approach developed here, a cost function, based on the modal settling times, is first established from the design objective. Next, the optimal performance indices from the sequential and concurrent designs are obtained by selecting the coefficients and locations of the vibration dampers. These performance indices are used to determine the design corresponding to the highest MDQ value, which gives the overall optimal design. For performance evaluation, optimal design of active vibration controllers is carried out, using the linear quadratic regulator (LQR), and its MDQ value is established. The results from two case studies show that optimal linear dampers designed using the MDQ approach can achieve the performance of an optimal active controller. This approach can also provide an insight into the performance degradation in each subsystem (or sub-problem) due to the dynamic coupling effects in the overall system.
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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 | 0.002 | 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".