Name
Abstract | ||
|---|---|---|
A feedback system is called improvable under budget constraints if its performance can be enhanced by reallocating instrumentation cost between sensors and actuators. An instrument (i.e., sensor or actuator) is called the bottleneck of a feedback system if its improvement leads to the largest improvement of the system performance index. In this paper, these concepts are applied to SISO feedback systems with saturating actuators and noisy sensors. The approach is based on an extension of LQG theory to systems with saturating actuators. Using this theory and assuming that more expensive actuators and sensors ensure less saturation and measurement noise, respectively, we derive an improvability and bottleneck indicator, which determines when and how the system can be improved. Illustrating examples are provided |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ACC.2001.945520 | American Control Conference, 2001. Proceedings of the 2001 |
Keywords | DocType | Volume |
actuators,feedback,linear quadratic gaussian control,performance index,sensors,lqg theory,siso,bottleneck,budget constraints,feedback system,improvable systems,instrumentation cost,measurement noise,noisy sensors,performance,saturating actuators,system performance,stochastic processes,budget constraint,indexation,noise measurement | Conference | 1 |
ISSN | ISBN | Citations |
0743-1619 | 0-7803-6495-3 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongsoon Eun | 1 | 0 | 0.34 |
| Pierre T. Kabamba | 2 | 90 | 62.98 |
| Semyon M. Meerkov | 3 | 43 | 7.19 |