Modified error decentralized control with observer backstepping
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Bibliographic record
Abstract
In this paper, an output feedback version of the modified error method is pre-sented, for linear coupled plants. The novelty lies in the combination of a modified control function of Lyapunov with the observer backstepping tech-nique to obtain a totally decentralized output feedback scheme. Furthermore, the design algorithm is presented in a new recursive form that goes beyond the general expressions yielded by the backstepping. The decentralization, i.e., the elimination of the cross-terms from the obtained multivariable controller, is rendered possible by a new choice of the regulated errors in the backstep-ping procedure. The internal stability and the tracking performances of the closed-loop system are still preserved, as long as the observer convergence is guaranteed and the H∞–norm of the plant interaction quotient is less than one. The developed scheme is successfully applied to the control of a rougher flotation phenomenological simulator. Key words: coupled plants, decentralized control, observer backstepping, Lyapunov functions. 1
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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 | 0.000 | 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 | 0.001 | 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