4.7 Article

Combined state and least squares parameter estimation algorithms for dynamic systems

Journal

APPLIED MATHEMATICAL MODELLING
Volume 38, Issue 1, Pages 403-412

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2013.06.007

Keywords

Dynamic system; Numerical algorithm; Least squares; Parameter estimation; Recursive identification; State space model

Funding

  1. National Natural Science Foundation of China [61273194]
  2. Natural Science Foundation of Jiangsu Province (China) [BK2012549]
  3. 111 Project [B12018]
  4. PAPD of Jiangsu Higher Education Institutions

Ask authors/readers for more resources

The control theory and automation technology cast the glory of our era. Highly integrated computer chip and automation products are changing our lives. Mathematical models and parameter estimation are basic for automatic control. This paper discusses the parameter estimation algorithm of establishing the mathematical models for dynamic systems and presents an estimated states based recursive least squares algorithm, and the states of the system are computed through the Kalman filter using the estimated parameters. A numerical example is provided to confirm the effectiveness of the proposed algorithm. (C) 2013 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available