Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
698051 | Automatica | 2009 | 6 Pages |
Abstract
In this paper, the problem of identifying linear discrete-time systems from noisy input and output data is addressed. Several existing methods based on higher-order statistics are presented. It is shown that they stem from the same set of equations and can thus be united from the viewpoint of extended instrumental variable methods. A numerical example is presented which confirms the theoretical results. Some possible extensions of the methods are then given.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Stéphane Thil, Wei Xing Zheng, Marion Gilson, Hugues Garnier,