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

Direct link
Tracking Performance Analysis of the Forgetting Factor RLS Algorithm
Academica Sinica, China.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Université Pierre et Marie Curie, France.
1992 (English)Report (Other academic)
Abstract [en]

The authors present a theoretical analysis for the performance of the standard forgetting factor recursive least squares (RLS) algorithm used in the tracking of time-varying linear regression models. Under some explicit excitation conditions on the regressors, it is shown that the parameter tracking error is on the order O(μ+γ2/μ), where μ=1-λ, λ is the forgetting factor, and γ is the quantity reflecting the speed of parameter variation. Furthermore, for a large class of weakly dependent regressors, simple approximations for the covariance matrix of this error are derived. These approximations are not asymptotic in nature: they hold over all time intervals and for all μ in a certain region.

Place, publisher, year, edition, pages
LiTH-ISY-I, ISSN 8765-4321 ; 1393
Keyword [en]
Adaption, Least squares, Tracking, Recursive identification
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-55226OAI: diva2:315925
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2013-07-30

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Ljung, Lennart
By organisation
Automatic ControlThe Institute of Technology
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

Total: 32 hits
ReferencesLink to record
Permanent link

Direct link