Discrete‐time ${\cal H}_{\rm 2}$ output tracking control of wireless networked control systems with Markov communication models
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
Abstract This paper considers the discrete‐time ${\cal H}_2$ output tracking control of wireless networked control systems (NCSs) where the time delays are modeled as Markov chains. Output tracking control can find many applications in industry. In order to reduce the conservativeness and achieve better performance, the designed state feedback controller is dependent on available sensor‐to‐controller and controller‐to‐actuator delays. Then, the formulated closed‐loop system is a special jump linear system governed by interdependent parameters of Markov chains and the condition for stochastic stability is proposed. By generalization of the ${\cal H}_2$ norm definition, new relation of the ${\cal H}_2$ norm for the special system is derived in terms of state space form. The condition of a set of linear matrix inequalities (LMIs) with nonconvex constraints is given to solve the ${\cal H}_2$ output tracking control problem. Simulation examples are provided to illustrate the effectiveness of the method. Copyright © 2009 John Wiley & Sons, Ltd.
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 | 0.001 | 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 | 0.001 | 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