Neural network‐based adaptive control of piezoelectric actuators with unknown hysteresis
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Bibliographic record
Abstract
Abstract This paper proposes a neural network (NN)‐based adaptive control of piezoelectric actuators with unknown hysteresis. Based on the classical Duhem model described by a differential equation, the explicit solution to the equation is explored and a new hysteresis model is constructed as a linear model in series with a piecewise continuous nonlinear function. An NN‐based dynamic pre‐inversion compensator is designed to cancel out the effect of the hysteresis. With the incorporation of the pre‐inversion compensator, an adaptive control scheme is proposed to have the position of the piezoelectric actuator track the desired trajectory. This paper has three distinct features. First, it applies the NN to online approximate complicated piecewise continuous unknown nonlinear functions in the explicit solution to Duhem model. Second, an observer is designed to estimate the output of hysteresis of piezoelectric actuator based on the system input and output. Third, the stability of the controlled piezoelectric actuator with the observer is guaranteed. Simulation results for a practical system validate the effectiveness of the proposed method in this paper. Copyright © 2008 John Wiley & Sons, Ltd.
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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) | 0.001 | 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