DocumentCode :
829278
Title :
Bootstrap estimation of parameters and states of linear multivariable systems
Author :
El-Sherief, H. ; Sinha, N.K.
Author_Institution :
McMaster University, Hamilton, Ontario, Canada
Volume :
24
Issue :
2
fYear :
1979
fDate :
4/1/1979 12:00:00 AM
Firstpage :
340
Lastpage :
343
Abstract :
A two-stage bootstrap algorithm is presented for on-line estimation of the parameters and states of a linear multivariable discrete-time system. A special canonical form of the state equations gives a pseudoparameter measurement equation the parameters of which are directly related to those of the canonical model. These parameters are estimated in stage 1 using a recursive least-squares algorithm. These parameter estimates are then utilized for estimating the states in stage 2 using stochastic approximation. The two stages are coupled in a bootstrap manner. The results of a simulated example are included.
Keywords :
Least-squares estimation; Linear systems, stochastic discrete-time; Parameter estimation; Recursive estimation; State estimation; Stochastic approximation; Adaptive filters; Detectors; Kalman filters; MIMO; Minimax techniques; Parameter estimation; Recursive estimation; State estimation; Stochastic processes; Stochastic systems;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1979.1102028
Filename :
1102028
Link To Document :
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