Name
Abstract | ||
|---|---|---|
In this paper we develop performance bounds on disturbance power reduction for multiple-input multiple-output networked feedback systems via an information-theoretic approach. The bounds are derived for a system setting with linear time-invariant plants and causal stabilizing controllers communicating over noisy communication channels. We utilize the notion of power gain to measure the worst-case power reduction from the disturbance to the error signal. Concepts from information theory such as entropy and mutual information are instrumental in the analysis, and the performance bounds can be quantified explicitly in terms of the channel blurredness, a measure of poorness on the channel quality, and the plant unstable dynamics. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | Information theory,Power gain,Computer science,Control theory,MIMO,Communication channel,Error signal,Mutual information,Control system,Instrumental and intrinsic value |
DocType | ISSN | Citations |
Conference | 0743-1546 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Song Fang | 1 | 36 | 7.89 |
| Jie Chen | 2 | 647 | 124.78 |
| Hideaki Ishii | 3 | 949 | 85.28 |