Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper addresses analysis and design issues in adaptive PID control for linear second-order minimal phase processes using the backstepping algorithm. The first step consists in adding an integral action to the basic backstepping algorithm to obtain a zero static error. An integrator is therefore added to the plant model and is then slid back to the controller equation at the end of the design. The control law is made adaptive without using a certainty-equivalence design and is robustified even more with nonlinear damping. The resulting adaptive PID control is uce+udyn+unld , where uce is what would be the output of the adaptive PID if a certainty-equivalence-based design were used, udyn compensates for the adaptation dynamics and unld is a nonlinear damping term added to increase the robustness by bounding the errors, even when the adaptation is off. The resulting PID controller is hence more robust and presents better transients than the basic certainty-equivalence PID version. An example compares the proposed PID to a certainty-equivalence PID.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it