Adaptive fuzzy funnel control for nonlinear systems with input deadzone and saturation
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Bibliographic record
Abstract
This paper, for the first time, focuses on the problem of funnel control for strict-feedback systems with input deadzone and saturation, simultaneously. A new smooth function in non-affine form is firstly proposed to approximate the non-smooth input deadzone and saturation and transformed into an affine form by the mean-value theorem. The unknown nonlinear functions and external disturbances are estimated by fuzzy logic systems. An improved funnel error is given and embedded in the procedure of controller design. Based on the backstepping method, an adaptive fuzzy funnel controller is constructed, which guarantees that the output tracking error falls within a pre-set funnel and all the signals in the closed-loop system are semi-globally uniformly and ultimately bounded. Simulation results demonstrate the effectiveness of the developed controller.
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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 | 0.001 | 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 | 0.001 |
| 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