A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control
Bibliographic record
Abstract
Hysteretic nonlinearity behavior ubiquitously occurs in mechanical systems, particularly in high-precision instruments, which severely degrades system output performance. Consequently, it is unavoidable to establish an accurate hysteretic model to describe the hysteretic characteristic of various mechanical systems and to compensate for the system error caused by hysteresis. The piezo-actuated mechanism is one of the most frequent mechanical systems that occurs hysteretic phenomenon, explained in detail in this survey. Bouc-Wen (BW) model has been popularly applied in modeling hysteretic attributes due to the outstanding advantage of simple structure and identification process. This paper presents the latest BW model applications and investigates different BW models, identification methods, and control strategies in light of various application demands based on the BW model systematically. In addition, this survey is meaningful in choosing an appropriate modeling approach and control means for system design according to the distinct requirements, and in providing future research direction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".