Switching Gain-Scheduled Proportional–Integral–Derivative Electronic Throttle Control for Automotive Engines
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes an application of the switching gain-scheduled (S-GS) proportional–integral–derivative (PID) control technique to the electronic throttle control (ETC) problem in automotive engines. For the S-GS PID controller design, a published linear parameter-varying (LPV) model of the electronic throttle valve (ETV) is adopted whose dynamics change with both the throttle valve velocity variation and the battery voltage fluctuation. The designed controller consists of multiple GS PID controllers assigned to local subregions defined for varying throttle valve velocity and battery voltage. Hysteresis switching logic is employed for switching between local GS PID controllers based on the operating point. The S-GS PID controller design problem is formulated as a nonconvex optimization problem and tackled by solving its convex subproblems iteratively. Experimental results demonstrate overall superiority of the S-GS PID controller to conventional controllers in reference tracking performance of the throttle valve under various scenarios.
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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 | 0.003 | 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