Accessibility navigation


Parameter tracking of time-varying Hammerstein-Wiener Systems

Feng, Y. and Hong, X. (2021) Parameter tracking of time-varying Hammerstein-Wiener Systems. International Journal of Systems Science. ISSN 0020-7721

[img] Text - Accepted Version
· Restricted to Repository staff only until 27 May 2022.

1MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1080/00207721.2021.1931546

Abstract/Summary

A two-stage identification algorithm is introduced for tracking the parameters in time-varying Hammerstein-Wiener systems. The Kalman filtering algorithm and parameter separation technique are employed in the proposed algorithm. The convergence analysis of this two-stage algorithm is provided. It is shown that the proposed algorithm can guarantee the boundedness of the parameter estimation error. Four simulation examples, including a practical system application of electric arc furnace, have been employed to validate the effectiveness of the proposed approaches, for a range of simulated time-varying characteristics.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:99204
Publisher:Taylor & Francis

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation