Adaptive Estimated Inverse Output-Feedback Quantized Control for Piezoelectric Positioning Stage
Bibliographic record
Abstract
Focusing on the piezoelectric positioning stage, this paper proposes an adaptive estimated inverse output-feedback quantized control scheme. First, the quantized issue due to the use of computer is addressed by introducing a linear time-varying quantizer model where the quantizer parameters can be estimated on-line. Second, by using the fuzzy approximator, the developed controller can avoid the identification of the parameters in the piezoelectric positioning stage. Third, by constructing the estimated inverse compensator of the hysteresis, the hysteresis nonlinearities in the piezoelectric actuator are mitigated; Fourth, the states observer is designed to avoid the measurements of the velocity and acceleration signals. The analysis of stability shows all the signals in the piezoelectric positioning stage are uniformly ultimately bounded and the prespecified tracking performance of the quantized control system is achieved by employing the error transformed function. Finally, a computer controlled experiments for the piezoelectric positioning stage is conducted to show the effectiveness of the proposed quantized controller.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".