Fractional delayed feedback for semi-active suspension control of nonlinear jumping quarter car model
Bibliographic record
Abstract
Off-road vehicles often experience severe vibrations caused by jumping. These impact dynamics demonstrate rich nonlinear behaviors, including chaotic vibrations, which are undesirable in vehicle performances. Semi-active suspensions are a promising method to eliminate chaos because of their lower energy consumption. However, semi-active suspensions impose passivity constraints that require robust controllers. In this study, a fractional delayed feedback (DF) control is proposed for a semi-active suspension. A quarter car model with jumping nonlinearity is considered as a typical off-road vehicle model. The performance and applicability of the proposed fractional DF are numerically analyzed. Performance analysis revealed that fractional DF effectively stabilized chaos into periodic motion in the presence of passivity constraints owing to the semi-active suspension. The stabilization range is affected by the controller parameters, particularly the fractional order. The applicability analysis revealed that the fractional DF is robust to forcing frequency variations and noise contamination. The results demonstrate that fractional DF has higher applicability in semi-active suspensions than conventional DF.
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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 | 0.000 | 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".