liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Adaptive Forgetting in Recursive Identification through Multiple Models
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1985 (English)In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 42, no 5, 1175-1193 p.Article in journal (Refereed) Published
Abstract [en]

A new recursive identification method, adaptive forgetting through multiple models (AFMM) is presented and evaluated using computer simulations. AFMM is especially suited for identification of systems with jumping or rapidly changing parameters. It can be viewed as a particular way of implementing adaptive gains or adaptive forgetting factors for recursive identification. The new method essentially consists of multiple recursive least-squares (RLS) algorithms running in parallel, each with a corresponding weighting factor. The simulations indicate that AFMM is able to track rapidly changing parameters well, and that the method is robust in several respects.

Place, publisher, year, edition, pages
Taylor & Francis, 1985. Vol. 42, no 5, 1175-1193 p.
Keyword [en]
Recursive identification, Adaptive Forgetting through Multiple Models, (AFMM), Simulations, Least-squares
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-100753DOI: 10.1080/00207178508933420OAI: diva2:663428
Available from: 2013-11-11 Created: 2013-11-11 Last updated: 2014-02-20

Open Access in DiVA

No full text

Other links

Publisher's full textRelated report
By organisation
Automatic ControlThe Institute of Technology
In the same journal
International Journal of Control
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 37 hits
ReferencesLink to record
Permanent link

Direct link