| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4637918 | Journal of Computational and Applied Mathematics | 2016 | 9 Pages |
Abstract
This paper focuses on the parameter and state estimation problems for observer canonical state space systems from measurement information, derives a Kalman filter based least squares iterative (KF-LSI) algorithm to estimate the parameters and states, and a model decomposition based KF-LSI algorithm to enhance computational efficiency. An example is provided to confirm the effectiveness of the proposed algorithms.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Feng Ding, Ximei Liu, Xingyun Ma,