LPV-Based Air-Fuel Ratio Control of Spark Ignition Engines Using Two Gain Scheduling Parameters
Bibliographic record
Abstract
The three way catalytic converter (TWC) is a critical component for the mitigation of tailpipe emissions of modern internal combustion (IC) engines. Because the TWC operates effectively only when the air-fuel ratio is very close to stoichiometric, accurate control of the air-fuel ratio is required. The dynamics of the IC engine can be modeled as a first order plus dead time for controller design purposes and vary with both engine speed and air flow. Traditional control schemes using time-invariant controllers have been successful in guaranteeing stability over the operating range of the engine but have introduced a degree of conservatism. To reduce the conservatism, a gain scheduling controller taking both engine speed and air flow as scheduling parameters is proposed. A linear parameter varying model of the plant is constructed and the controller design method is formulated in terms of linear matrix inequalities yielding a convex optimization problem. The resulting closed-loop system has guaranteed stability and performance over the designed operating range of the engine. Simulations are performed to validate and compare the controller with a time-invariant controller as well as a gain scheduling controller that takes only engine speed as a scheduling parameter.
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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 | 0.001 |
| 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".