Name
Abstract | ||
|---|---|---|
A new method is presented for the identification of systems parameterized by linear state spacemodels. The method relies on the concept of subspace fitting, wherein an input/output data modelparameterized by the state matrices is found that best fits, in the least-squares sense, the dominantsubspace of the measured data. Some empirical results are included to illustrate the performanceadvantage of the algorithm compared with standard techniques.1. IntroductionResearch in the... |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1109/9.341800 | Automatic Control, IEEE Transactions |
Keywords | DocType | Volume |
Hankel matrices,MIMO systems,identification,least squares approximations,linear systems,state-space methods,MIMO systems,identification,input/output data model,least-squares,linear state-space models,state matrices,subspace fitting method,time invariant linear systems | Journal | 40 |
Issue | ISSN | Citations |
2 | 0018-9286 | 4 |
PageRank | References | Authors |
2.78 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Swindlehust, A. | 1 | 4 | 2.78 |
| Roy, R. | 2 | 4 | 2.78 |
| Björn E. Ottersten | 3 | 6418 | 575.28 |
| Kailath, T. | 4 | 4 | 2.78 |