DocumentCode :
1359969
Title :
Restricted-structure linear estimators for multiple-model systems
Author :
Grimble, M.J.
Author_Institution :
Ind. Control Centre, Strathclyde Univ., Glasgow, UK
Volume :
147
Issue :
3
fYear :
2000
fDate :
6/1/2000 12:00:00 AM
Firstpage :
193
Lastpage :
204
Abstract :
A new class of discrete-time optimal linear estimators is introduced for multiple-model systems that minimises a minimum-variance criterion but where the structure is prespecified to have a simple low-order form. The restricted-structure estimator can be of much lower order than a Kalman (1961) or Wiener (1949) estimator and it minimises the estimation-error variance, subject to the constraint referred to. The numerical optimisation algorithm is simple to implement and full-order optimal solutions are available as a by-product of the analysis. The algorithm enables low-order optimal estimators to be computed that directly minimise the cost index across a set of possible linear signal or noise source models. The main technical advances lie in the theoretical analysis that enables the expanded cost expression to be simplified before the numerical solution is obtained, and the extension of the restricted-structure optimisation technique to multiple-model systems
Keywords :
Kalman filters; Wiener filters; adaptive estimation; optimisation; parameter estimation; signal processing; Kalman estimator; Wiener estimator; X-ray gauge measurements; adaptive estimator; cost index minimisation; discrete-time optimal linear estimators; estimation-error variance; expanded cost expression; frequency-domain approach; full-order optimal solutions; linear signal models; low-order optimal estimators; low-order structure; minimum-variance criterion; multiple-model systems; noise source models; numerical optimisation algorithm; numerical solution; optimal linear filtering; restricted-structure linear estimators; restricted-structure optimisation; rolling mill; signal processing;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:20000366
Filename :
852300
Link To Document :
بازگشت