Parameterized Regulator Design Method for Switched Linear Systems
Bibliographic record
Abstract
In this paper, a parameterized regulator design method based on bilinear matrix inequalities (BMIs) is presented for switched linear systems, where it is desired to reject known disturbance signals and/or track known reference inputs. Switching among plant models as well among disturbance and reference signals is defined according to a switching surface. The regulator design approach consists of three steps. The first step consists of constructing a switched observer-based state-feedback central controller for the switched linear system. Switching in the controller is performed according to the same switching rule as in the plant. The second step involves augmenting the switched central-controller to construct a parameterized set of switched controllers. Conditions for internal stability of the resulting switched closed loop system are presented. In the third step, regulation conditions are derived for the switched closed loop system. Based on the regulation conditions, a regulator synthesis approach is proposed based on solving properly formulated BMIs. Finally, a numerical example is presented to illustrate the performance of the proposed regulator.
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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 | 0.001 | 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 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".