Name
Abstract | ||
|---|---|---|
The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this approach usually leads to a transfer function estimate with relative degree 1, independent of the relative degree of the strictly proper real system. In this paper, a refinement of these methods is developed. Inspired by the indirect prediction error method, we propose an estimator that enforces a fixed relative degree in the continuous-time transfer function estimate, and show that the estimator is consistent and asymptotically efficient. Extensive numerical simulations are put forward to show the performance of this estimator when contrasted with other indirect and direct methods for continuous-time system identification. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CDC.2018.8619141 | 2018 IEEE Conference on Decision and Control (CDC) |
Keywords | DocType | Volume |
System identification,Continuous-time systems,Parameter estimation,Sampled data | Conference | abs/1803.08449 |
ISSN | ISBN | Citations |
0743-1546 | 978-1-5386-1396-2 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto González | 1 | 33 | 9.74 |
| Cristian R. Rojas | 2 | 252 | 43.97 |
| James S. Welsh | 3 | 17 | 6.59 |