DocumentCode :
839742
Title :
Convergence and rate of convergence of a recursive identification and adaptive control method which uses truncated estimators
Author :
Kushner, Harold J. ; Kumar, Rajendra
Author_Institution :
Brown University, Providence, RI, USA
Volume :
27
Issue :
4
fYear :
1982
fDate :
8/1/1982 12:00:00 AM
Firstpage :
775
Lastpage :
782
Abstract :
A stochastic approximation-like method is used for the recursive identification of the coefficients in y_{n}=\\sum \\min{1}\\max {l_{1}}a_{i}y_{n-i}+\\sum \\min{0}\\max {l_{2}}b_{i}u_{n-i}+ \\sum \\min{1}\\max {l_{3}}c_{i}w_{n-i}+w_{n} , where {w_{n}} is a sequence of mutually independent and bounded random variables, and is independent of the bounded {u_{n}} . Such methods normally require the recursive estimation of the "residuals" or the {w_{n}} , and the algorithms for doing this can be unstable if the parameter estimates are not close enough to their true values. The problem is solved here by use of a simple truncated estimator, which is probably what would be used in implementation in any, case. Then, under a stability, and strict positive real type condition, with probability 1 (w.p.1) convergence is proved and the rate of convergence is obtained. An associated adaptive control problem is also treated.
Keywords :
Adaptive control, linear systems; Parameter identification, linear systems; Recursive estimation; Adaptive control; Convergence; Helium; Iterative methods; Parameter estimation; Programmable control; Random variables; Recursive estimation; Stability; Stochastic processes;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1982.1103039
Filename :
1103039
Link To Document :
بازگشت