Name
Abstract | ||
|---|---|---|
In this paper, we consider the problem of actively identifying the state of a stochastic dynamic system over a finite horizon. We formalize this Problem as a Stochastic Optimal Control one, in which the minimization of a suitable uncertainty measure is performed. To this end, the use of the Renyi Entropy is proposed and motivated. A neural control scheme, based on the application of the Extended Ritz Method and on the use of a Gaussian Sum Filter, is then presented. Simulation results show the effectiveness of the approach. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/CDC.2005.1582873 | conference on decision and control |
Keywords | DocType | ISSN |
optimal control,entropy,renyi entropy,nonlinear systems,control systems,stochastic processes,cost function,measurement uncertainty,nonlinear system,stochastic optimal control | Conference | 0743-1546 |
ISBN | Citations | PageRank |
0-7803-9567-0 | 0 | 0.34 |
References | Authors | |
5 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| marco baglietto | 1 | 0 | 0.34 |
| d garassino | 2 | 0 | 0.34 |
| luca scardovi | 3 | 0 | 0.34 |
| l zanchi | 4 | 0 | 0.34 |
| R. Zoppoli | 5 | 279 | 51.51 |