DocumentCode
3424001
Title
The Kalman filter based recursive algorithm: windup and its avoidance
Author
Cao, Liyu ; Schwartz, Howard M.
Author_Institution
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont., Canada
Volume
5
fYear
2001
fDate
2001
Firstpage
3606
Abstract
A theoretical analysis is given which shows that the covariance matrix in the Kalman filter based parameter estimator increases at least linearly when the input is not persistently exciting. This windup phenomenon which is the same as that in the exponential forgetting least squares algorithm, is undesirable and even unacceptable in some applications. To overcome it a new algorithm is proposed, in which the constant covariance matrix of the parameter variation is replaced by a time-varying sequence consisting of the regression vector
Keywords
Kalman filters; covariance matrices; filtering theory; least squares approximations; parameter estimation; Kalman filter; covariance matrix; least squares; parameter estimation; recursive algorithm; windup; Algorithm design and analysis; Covariance matrix; Drives; Eigenvalues and eigenfunctions; Least squares approximation; Least squares methods; Parameter estimation; Recursive estimation; Systems engineering and theory; Windup;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2001. Proceedings of the 2001
Conference_Location
Arlington, VA
ISSN
0743-1619
Print_ISBN
0-7803-6495-3
Type
conf
DOI
10.1109/ACC.2001.946194
Filename
946194
Link To Document