Real‐time hybrid control of electrohydraulic active suspension
Bibliographic record
Abstract
Summary Electrohydraulic actuators are an attractive choice for active suspension, because these systems provide a high power‐to‐weight ratio. However, their dynamics are highly nonlinear. In addition, the use of one simple controller for both position and force is complicated, because there is a compromise between them in the case of active suspension. Most existing controllers do not efficiently fulfill the requirements, because only one state variable is considered. In this paper, we address these problems by developing a new hybrid controller for both position and force and implementing it in a real‐time test bench. Our goal is to control the vertical position of the passenger seat while tracking the force transmitted to passengers and keeping it within tolerable and comfortable limits. Therefore, the proposed controller is a combination of two controllers. Its flexible structure redirects the control signal to control the proper controlled state variable. The real‐time results of the newly designed hybrid controller are compared with those obtained using a classical proportional integral derivative controller, because this is the most widely used controller in the industry. As expected, the proposed controller demonstrates better performance in real‐time operation. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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) | 0.001 | 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".